Brazil nut consumption within an energy-restricted diet improved cardiometabolic risk markers in women: a quasi-experimental, controlled study (Brazilian Nuts Study)

Abstract

Consuming functional foods alongside the energy-restricted diet can be a great ally in weight loss and improving cardiometabolic risk factors. Whether Brazil nut (BN) consumption in the context of energy restriction affects them remains to be answered. We aimed to evaluate the effect of BN within an energy-restricted diet on cardiometabolic risk markers among women. This is an eight-week, quasi-experimental, controlled nutritional intervention study. The women were allocated into two energy-restricted (-500 kcal/d) groups: a control free of BN (n=29) and a BN-group (BNG) (n=27) with 2 units/day of BN (~ 347 µg of selenium). Both groups had similar weight loss, but in the BNG, the serum selenium increased by 276.7% and apolipoprotein A1 increased by 27.4%. In addition, BNG had a more pronounced reduction in liver enzymes, and presented the most preserved percentages of lean and fat-free mass in relation to the control group. Consuming 2 units/day of BN in an 8-week weight loss intervention improved cardiometabolic risk markers in women. Our results suggest that regular consumption of BN during energy-restricted diets may be a strategy to minimize adiposity, preserve lean mass, improve serum selenium status, lipid, and liver metabolism markers, and, consequently, help obesity management and its comorbidities.

Key words
apolipoproteins; free-fat mass; obesity; oilseeds; selenium; weight loss

INTRODUCTION

Although obesity has a multifactorial etiology, biologically, the excess energy ingested in parallel with decreased energy expenditure lead to weight gain and increased adiposity (Lin & Li 2021). Some systemic effects can be improved with even a modest 2-5% weight loss (Ryan & Yockey 2017). Lifestyle change, which includes adherence to healthy eating habits and regular physical activity, is the basis of obesity treatment (Raynor & Champagne 2016, Pepe et al. 2023). Despite limitations such as low long-term adherence and possible weight regains (Busetto et al. 2021), among other limitations common to other weight loss strategies, a balanced energy-restricted diet is the most well-established current nutritional recommendation for weight loss available in the literature (Varkevisser et al. 2019, Pepe et al. 2023). Parallel to energy restriction, the insertion of functional foods rich in fiber, unsaturated fats, and proteins can be great allies in the weight loss and related-cardiometabolic risk process (Caldas et al. 2022).

In turn, functional foods alone, such as nuts, do not lead to weight loss, but they can be beneficial in controlling satiety and increasing thermogenesis (Natoli & McCoy 2007, Schincaglia et al. 2017, Estrada et al. 2022). The consumption of Brazilian nuts (Bertholletia excelsa H.B.K and Anacardium occidentale L.) and almonds (Prunus dulcis M.) combined with an energy-restricted diet did not lead to greater weight loss but improved body composition, especially in maintaining lean mass (Caldas et al. 2022) and decreasing fat mass (Dhillon et al. 2016). Despite this evidence, no study has evaluated the isolated effects of Brazil nut (BN), a food source of selenium, combined with an energy-restricted diet on cardiometabolic risk markers. BN is a nut native to the Amazon biome, and like other nuts, it is a food with concentrated bioactive compounds such as fibers, proteins, phytochemicals, and unsaturated fats (Cardoso et al. 2017), in addition to it is one of the richest sources of selenium. This mineral is essential in redox homeostasis, the immune system, and endogenous cholesterol production (Alcântara et al. 2022). Studies also suggest that selenium participates in adipogenesis (Tinkov et al. 2020) and, therefore, may influence body composition.

BN has well-established beneficial effects on improving antioxidant status, inflammation, lipid profile, and oxidative stress, mainly attributed to its high selenium content (Cardoso et al. 2016, da Silva et al. 2022). All these benefits vary between studies and the health status of the subjects evaluated and have been documented when BN is consumed in the context of the usual diet (da Silva et al. 2022). Whether BN consumption has all these benefits when placed in the context of energy restriction remains to be answered (da Silva et al. 2022).

Thus, we aimed to evaluate the effect of BN intake within an energy-restricted diet on weight-loss and cardiometabolic risk markers. Second, we evaluated cardiometabolic risk markers according to variations in serum selenium levels.

MATERIALS AND METHODS

Study design and ethical approval

The present study is a quasi-experimental, controlled eight-week nutritional intervention trial conducted in free-living conditions with women with overweight or obesity (Figure 1). This study is in accordance with the Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) guideline (Des Jarlais et al. 2004).

Figure 1
Tables SI-SV.

The study occurred in the Department of Nutrition and Health of the Universidade Federal de Viçosa (UFV), Minas Gerais, Brazil, with enrollment between August 2018 and September 2021. This study was conducted according to the Resolution CSN 466/2012 and Declaration of Helsinki (1964) and all procedures involving human subjects were approved by the local ethical committee of the UFV (ethics number: 2.832.601/2018 for study 1 and 3.649.033/2019 for study 2). Written informed consent was obtained from all subjects. This study also is registered in the Brazilian Registers of Clinical Trials – REBEC (protocols: RBR-3ntxrm; http://www.ensaiosclinicos.gov.br/rg/RBR-3ntxrm/ and RBR-8zfn5c; https://ensaiosclinicos.gov.br/rg/RBR-8zfn5c).

This study is part of a major project called “Brazilian nuts study”. This study is the second trial of the Brazilian Nuts Study. In the first trial, a randomized clinical trial was conducted with the aim of evaluating the effect of a mixed Brazilian nuts (Brazil nut + cashew nuts) allied to an -500-kcal energy-restricted diet on cardiometabolic markers of women with overweight/obesity (http://www.ensaiosclinicos.gov.br/rg/RBR-3ntxrm/). The results of this study were previously published (Caldas et al. 2022). Thus, in this randomized study, the control group received a diet restricted to -500 kcal and free of nuts. On the other hand, in this second trial of the Brazilian Nuts Study, our aim was to evaluate the effect of only Brazil nut allied to an -500-kcal energy-restricted diet on cardiometabolic markers of overweight/obese women (https://ensaiosclinicos.gov.br/rg/RBR-8zfn5c). In this study, the control group was the same as that used in the first part of the “Brazilian nuts study” project, since the comparison group would be the same (only a diet restricted to -500 kcal and free of nuts). Therefore, the present article comprises data collected at 2 different moments of the “Brazilian nuts study” project and is a non-randomized, controlled clinical trial.

Subjects, recruitment, and sample calculation

Adult women (20-55 years) with overweight (BMI ≥ 27 kg/m2 and <30 kg/m2), waist circumference ≥ 80 cm, and body fat percentage ≥ 32% associated with at least one another component of metabolic syndrome: triglycerides ≥150 mg/dL, high arterial blood pressure (≥130/85 mmHg) or high fasting glucose (≥100 mg/dL); or women with obesity (BMI ≥ 30 kg/m²), high waist circumference (≥ 80 cm), and excess body fat percentage (≥ 32%) with or without metabolic complications were included. Non-inclusion criteria comprised pregnant, lactate, or menopausal women; athletes; vegans; smoking; women with a history of HIV, illness or digestive, liver, kidney, cardiovascular, thyroid, cancer, inflammatory diseases, and eating disorders; history of drug and/or alcohol abuse; aversion or allergy to nuts; infectious episode in the last month; use of anti-inflammatory drugs, corticosteroids, antibiotics, and others that may affect energy appetite and metabolism; body weight instability (5% of usual weight) in the last three months; regular consumption of any quantity of BN; alcohol consumption higher than 21 units (168g) per week; dental problems that interfere with chewing; regular use of vitamin, mineral, and omega-3 supplements (Caldas et al. 2022).

Participants were recruited in the city of Viçosa, Minas Gerais, Brazil and in neighboring cities. The recruitment methods were advertisements in social media (Instagram©, Facebook©, and WhatsApp©) and local radio and TV. After an initial screening, the women who met the essential eligibility criteria (age, BMI, no pregnancy, menopausal, and medical/supplement use) were invited to a face-to-face visit to evaluate their health history, physical activity level, and anthropometry (Caldas et al. 2022).

The primary outcome measure was weight-loss. The sample size was calculated on GPower software 3.1.9.7 version, using data from a similar intervention study entitled “The effect of almonds on anthropometric measurements and lipid profile in overweight and obese females in a weight reduction program: A randomized controlled clinical trial” (Abazarfard et al. 2014). The sample size was estimated considering an effect size d of approximately 0,74 kg (weight mean difference of -3.68 (SD 2.82) kg for the almond-enriched diet group and -1.27 (SD 3.62) kg for the nut-free diet group), the statistical power of 95%, two-sided α, and power of 80%. The estimated number of participants required in each group to answer our research question is at least 28 participants.

Dietary interventions

Women were allocated into two groups: 1) control group, which was instructed to consume an energy-restricted diet (-500 kcal/day) free of nuts and 2) the Brazil nut group (BNG), which was asked to follow the energy-restricted diet (-500 kcal/day) containing approximately 8g (two units) of BN daily. Participants were monitored via WhatsApp® and in a face-to-face consultation 30 days after the start of the intervention. In the 30-day consultation, a 24-hour food recall was applied to check compliance, questions regarding physical activity, medication use, difficulties, and progress of the prescribed food plan. All women were instructed to maintain their lifestyle and medications during the study and to inform the research team of any changes in the type or dosage of the ongoing medication.

Energy-restriction

Total energy intake was estimated for each participant using the Estimated Energy Requirement (EER) for adult women with overweight/ obesity (Jensen et al. 2014). Then, 500 kcal/day was deducted from the dietary prescription to achieve a loss of 2 kg per month. Participants received an individualized eating plan with five nutritionally-balanced menus, each with five meals (breakfast, morning snack, lunch, afternoon snack, and dinner). The average distribution of carbohydrates, protein, and lipids was 50.0%, 20.0%, and 30.0% of daily energy, respectively, in accordance with recommendations of obesity management guidelines (Jensen et al. 2014, Caldas et al. 2022). An example of a prescribed menu for the control and BNG containing ~1,800 kcal/day is presented in the Supplementary Material – Table SI.

For the BNG, the diets included the energy provided by the daily portion of 8 g (2 units/day) of BN. To balance the diets in macronutrients, total, polyunsaturated, saturated, and total fats, the control group was instructed to consume a sauce based on soybean oil and lemon (2:1 ratio, respectively). On the other hand, the BNG was oriented to consume a sauce based on canola oil and lemon (2:1 ratio, respectively). Sauces were provided by the research team and handed out to women fortnightly.

Brazil nut

The BN used in the study was donated by ECONUT© (https://econut.com.br/). The BN is fresh, organic, grown at Fazenda Aruanã, located in the municipality of Itacoatiara, state of Amazonas, Brazil. All BN were received in modified atmosphere packages and portioned (two units) in laminated packages, vacuum sealed (Selovac Sealer model 200 B), and stored in a freezer at -20°C until distribution to the participants.

The amount of two units of BN used in this study was defined based on its selenium content not exceeding the Tolerable Upper Intake Level (UL) of the mineral, which is 400 µg/day. Brazil nut used in this study is a food source of selenium and we do not consider them as a supplement. Furthermore, evidence has shown the beneficial effects of BN consumption with a minimum selenium content of 290 µg for women with obesity (Cominetti et al. 2011, 2012). Each BN unit used in our study had 173.6 µg of selenium, measured by inductively coupled plasma atomic emission spectrometry determination of elements in food using Microwave Assisted Digestion. Then, we doubled the number of BN to approximate the amount of selenium contained in the nuts from previous studies, which did not exceed the UL.

We also assessed the lipid profile of our BN by gas chromatography following the protocol proposed by Folch et al. (1957) and Hartman & Lago (1973). Monounsaturated, polyunsaturated, and saturated fatty acids represent 18.7 %, 48.2 %, and 33.1% of total fat in BN, respectively (Table SII). The total content of selenium prescribed in the diet including the 2 units of BN was 375.75 µg, while for the control group was 28,55 µg (Table SI).

Data collection

The participants were instructed to go to the Health Service of the Universidade Federal de Viçosa (UFV), fasting for 10 to 12 hours before and at the end of the nutritional intervention period for blood collection and assessment of anthropometry and body composition using Dual-energy X-ray absorptiometry (DEX). Anthropometry, physical activity practice, and food intake were evaluated at the Laboratory of Energy Metabolism and Body Composition (LAMECC) located in the Department of Nutrition and Health at UFV.

The BNG and the control group had the same number of consultations throughout the intervention period. In general, three main presential consultations were carried out for the two groups. The first consultation was used to conduct initial assessments. Then, after 1 month of intervention, participants were invited to come to LAMECC to have their anthropometric measurements and food consumption measured. This second visit was a monitoring visit and a time to clarify any doubts. Finally, after 2 months of intervention, the final evaluations were carried out in a similar way to the initial evaluation. All participants, both from the BNG and the control group, had access to the team’s WhatsApp number and could clarify any specific doubts.

Anthropometry and body composition

At the first and last consultations, body weight (kg), height (m), waist circumference (WC) (cm), hip circumference (cm), and neck circumference (cm) were measured. Body weight was assessed by Inbody 230 (Biospace Corp., Seoul, South Korea). The height was measured using a stadiometer (Seca 206 model, Hamburg, Germany). BMI was obtained through the ratio between weight in kg and squared height in meters. Waist circumference was measured at the umbilicus waist at the end of normal expiration using an inelastic tape (precision 0.1 cm). Hip and neck circumferences were measured utilizing an inelastic tape at the maximum posterior extension of the gluteus and in the middle of the neck, respectively. Waist-to-height ratio (WHtR) was obtained through the ratio between WC and height in cm. Deep-Abdominal-Adipose-Tissue Index (DAAT, cm2) was calculated through the equation for women: - 278 + [- 0.86 x weight (kg)] + [5.19 x WC (cm)] (Brundavani et al. 2006).

DEX (Lunar Prodigy Advance DXA System, GE Lunar) was used for body composition assessment. To ensure the reliability of the DEX exam, the participants were instructed on the exam days: to wear light clothes, remove any metal accessories (earrings, piercings, rings, etc.), not to be menstruating, not to do activities that require effort, and be in total fasting for at least 10 hours. Values in kilograms of fat mass (FM), fat-free mass (FFM), lean mass (LM), and total mass were obtained from the total body and regions such as trunk, android, and gynoid. Posteriorly, the percentages were calculated in relation to total body measurements (Table SIII). The android area is between the ribs and the pelvis, while the gynoid region includes the hips and upper thighs and overlaps the leg and truncal regions. Body mass changes refer to the ∆ value obtained through the final assessment minus baseline.

Cardiometabolic markers

Variables such as adiposity indexes, glucose, lipid and liver markers were considered cardiometabolic risk markers.

Serum total cholesterol, low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), triglycerides, and glucose were analyzed by colorimetric method. Very low-density lipoprotein cholesterol (VLDL-c) was calculated using the Friedewald equation (Friedewald et al. 1972). Serum glucose, aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), and alkaline phosphatase were analyzed using the enzymatic method. Serum insulin was determined by the chemiluminescence method. Serum Apolipoprotein E was determined by the immunonephelometry method. Apolipoproteins A1 (Apo A1) and B (Apo B) were measured by the Turbidimetry method. Apo A1 is the main protein component of HDL, while Apo B is the main protein component of LDL. In turn, Apo E is involved in the redistribution of triglycerides and cholesterol (Faludi et al. 2017).

Total cholesterol minus HDL-c was calculated to obtain non-HDL-c. Total cholesterol/HDL, LDL/HDL, and Apo B/Apo A1 ratios were also estimated. HOMA-IR was calculated using the formula: fasting glucose (mg / dl) x fasting serum insulin (μU / ml) / 405 (Wallace & Matthews 2002). The triglyceride-glucose index (TyG index) was calculated using the formula: Ln [triglycerides (mg / dl) x fasting blood glucose (mg / dl) / 2]. The TyG index is a surrogate method for assessing insulin resistance validated against HOMA-IR (Simental-Mendía et al. 2008). Fatty liver index (FLI) was estimated through the equation (e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (GGT) + 0.053*waist circumference - 15.745) / (1 + e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (GGT) + 0.053* waist circumference - 15.745) * 100. This index is a simple and accurate predictor of hepatic steatosis (Bedogni et al. 2006).

Serum selenium (µ/L) was determined using inductively coupled plasma mass spectrometry according to standardized protocols.

Visceral adiposity index (VAI) was calculated through the formula for women: [WC (cm) / (36.58 + 1.89 x BMI (kg/m²))] x (triglycerides (mmol/L) / 0.81) x (1.52 / HDL (mmol/L)) (Amato et al. 2010). According to standardized protocols, serum selenium (µ/L) was determined using inductively coupled plasma mass spectrometry.

Dietary assessment and physical activity

To assess food consumption, participants were instructed to complete three-day food records (two non-consecutive weekdays and one weekend day) before the start of the nutritional intervention period. A dietitian checked all reported food and its respective quantities. In the 60-day consultation, a 24-hour food recall was applied by a dietitian. REC24h-ERICA® software (Barufaldi et al. 2016) was used to enter the food record. The software has a database composed of a list of items included in the database of food and beverage purchases from the Pesquisa de Orçamentos Familiares (POF – Brazilian Household Budget Survey). The interviewers added the food items that were not contained in the database. Then, estimated energy and nutrients intake were obtained.

Physical activity was assessed using the short version of the International Physical Activity Questionnaire (IPAQ). Subjects were assessed according to three categories of physical activity (low, moderate, or high activity levels). Then, the results in MET minutes a week were calculated. MET minutes represent the amount of energy expended carrying out physical activity. A MET is a multiple of your estimated resting energy expenditure. One MET is what you expend when you are at rest. Therefore, 2 METS is twice what you expend at rest. To get a continuous variable score from the IPAQ (MET minutes a week) we considered walking to be 3.3 METS, moderate physical activity to be 4 METS, and vigorous physical activity to be 8 METS (Forde 2018).

Statistical analysis of anthropometric markers, body composition indicators, and cardiometabolic risk markers

Statistical analysis was performed using the Statistical Package for Social Sciences (SPSS), version 21.0 for Windows. The distribution of quantitative variables was performed following the principles of the Gaussian distribution. Thus, the Shapiro-Wilk test was performed for each group of interventions. Continuous variables were described as mean, standard deviation, or median, and 95% confidence interval. Parametric variables were compared within and between groups using the paired t-test and Student’s t-test, respectively. Non-parametric variables were compared within and between groups using the Wilcoxon test and the Mann-Whitney, respectively. Analysis of covariance (ANCOVA) adjusted by baseline value was used to compare means between groups when the variable differed between groups at baseline. The level of significance in two-tailed tests was set at 5%.

RESULTS

Two hundred and two women were recruited between August 2018 and September 2021, but one hundred and forty-six did not meet the inclusion criteria or showed no interest in participating. A total of fifty-six women initiated the study, and forty-nine concluded. Twenty-nine women were allocated to the control group and twenty-seven to the BNG. The dropout in the follow-up was 17.2% in the control group and 7.4% in the BNG. 100% of the dropout were for personal reasons (Figure 1). The characteristics of women who initiated the intervention were similar at baseline compared with those who were lost to follow-up (Table SIV). We identified a power of 99% considering the mean difference in weight loss in the BNG (effect size = -1.7305 kg), bilateral α of 5 % and sample size of the group. Women included in the study were 33.9 (SD 7.5) years old and had a BMI of 33.4 (SD 4.3) kg/m².

Food consumption and physical activity

Consumption of carbohydrates and SFA significantly decreased in the control group after the intervention, and MUFA and SFA decreased while fiber and selenium intake increased after BN consumption, compared to baseline. Intake of energy, macronutrients, MUFA, PUFA, SFA and fiber did not differ between groups after the intervention. On the contrary, selenium intake was higher in the BNG that the control group (Table I), as expected. Physical activity levels did not change in either group during the intervention period (Table II).

Table I
Change in nutrient intake according to 8-wk energy-restricted diet (control vs. BN).

Energy and nutrients intake	Control group (n=24)	BNG (n=25)	p-value
Caloric deficit, kcal	-743.83 (625.94875.73)	-530.78 (325.05;795.17)	0.119
Total energy intake, kcal	-66.92 (-544.76;66.18)	-334 (-561.71;30.03)	0.544
Carbohydrate, g	-35.68 (-77.2;-4.53)*	-21.94 (-62.83;14.36)	0.528
Protein, g	-4.42 (-21.78;9.22)	-14.69 (-22.52;6.54)	0.481
Total fat, g	-0.4 (-18.6;9.55)	-2.77 (-21.87;0.2)	0.296
MUFA†, g	-2.67 (-8.97;2.98)	-3.22 (-7.87;0.21)*	0.811
PUFA, g	5.43 (-0.007;6.91)	0.36 (-2.83;2.79)	0.548
SFA, g	-5.92 (-10.53;-0.36)*	-4,79 (-9.38;-1.92)*	0.981
Fiber, g	0.85 (-5.36;5.62)	1.61 (0.54;6.82)*	0.576
Selenium, µg	11.45 (-28.96;18.98)	328.91 (304.71;361.81)**	≤0.001

• Values are median (95% CI). Change is the final assessment minus baseline. * p < 0.05 or ** p ≤ 0.001 are significant differences within-group (Wilcoxon test). p-values refer to the comparison between groups (Mann-Whitney). For variables different between groups at baseline†, p-value was obtained through ANCOVA analysis adjusted by baseline value. Values with a minus sign indicate negative values. BNG, brazil nut group; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid; SFA, saturated fatty mass.

Table II
Change in anthropometry and body composition according to 8-wk energy-restricted diet (control vs. BNG).

	Control group (n=24)		BNG (n=25)		Baseline p-value	∆ p-value
	Baseline	∆	Baseline	∆
Age, y	32.83 (7.85)	-	34.92 (7.26)	-	0.339	-
Weight, kg	90.64 (15.76)	-2.49 (2.41) **	85 (9.33)	-3.25 (2.49) **	0.138	0.284
BMI, kg/m²	34.21 (5.12)	-0.94 (0.9) **	32.65 (3.2)	-1.28 (0.99) **	0.205	0.219
WHtR	0.68 (0.07)	-0.02 (0.02) **	0.66 (0.05)	-0.03 (0.02) **	0.504	0.072
VAI	2.25 (2.04)	0.04 (0.59)	1.99 (0.97)	0.21 (0.7)	0.576	0.393
DAAT, cm²	216.94 (52)	-16.64 (15.2) **	207.61 (38.23)	-24.45 (14,84) **	0.480	0.081
Conicity index	7.43 (0.56)	-0.02 (0.03) **	7.24 (0.34)	-0.04 (0.04) **	0.167	0.076
Truncal FM, kg	23.41 (5.84)	-1.34 (2.08) *	21.72 (4.78)	-1.52 (1.61) **	0.303	0.748
Android FM, kg	3.83 (0.8)	-0.29 (0.23) **	3.2 (0.66)	-0.29 (0.26) **	0.008	0.627
Gynoid FM, kg	8.46 (2.15)	-0.32 (0.47) *	7.34 (1.1)	-0.27 (0.36) **	0.045	0.909
Total FM, kg	44 (9.36)	-1.44 (2.05) *	39.92 (6.52)	-2.14 (1.67) **	0.102	0.230
Truncal LM, kg	20.72 (3.76)	-1.5 (1.46) **	20.53 (3.07)	-0.57 (1.3) *	0.856	0.029
Android LM, kg	3.02 (0.59)	-0.23 (0.18) **	2.84 (0.46)	-0.02 (0.21)	0.264	0.002
Gynoid LM, kg	6.42 (1.19)	-0.26 (0.36) *	6.02 (1)	-0.07 (0.35)	0.236	0.103
Total LM, kg	41.59 (6.11)	-1.3 (1.57) *	41.28 (5.19)	-0.78 (1.71) *	0.858	0.336
Truncal FFM, kg	21.7 (3.82)	-1.46 (1.39) **	21.53 (3.04)	-0.57 (1.17) *	0.869	0.032
Android FFM, kg	3.08 (0.58)	-0.23 (0.18) **	2.9 (0.45)	-0.02 (0.21)	0.266	0.002
Gynoid FFM, kg	6.71 (1.23)	-0.25 (0.35) *	6.31 (1.01)	-0.07 (0.34)	0.247	0.101
Total FFM, kg	44.43 (6.33)	-1.23 (1.41) *	44.06 (5.22)	-0.79 (1.57) *	0.838	0.304
METs, min. week	547.87 (668.97)	-97.54 (512.50)	502.29 (698.69)	-87.81 (364.35)	0.822

• Values are mean (SD). Δ = final assessment – baseline. * p < 0.05 or ** p ≤ 0.001 are significant differences within-group (paired t-test). Baseline p-values and Δ p-values refer to the comparison between groups (Student t-test). BNG, brazil nut group; BMI, body mass index; WHtR, waist-to-height ratio; VAI, visceral adiposity index; DAAT, deep abdominal adipose-tissue; FM, fatty mass; LM, lean mass; FFM, fat-free mass.

Weight-loss and other results of anthropometric and body composition indicators

Weight, BMI, WHtR, WC, NC, HC, DAAT, and android fat mass (%) decreased in both groups after 8-wk energy-restriction intervention (Table II and Figure 2a). Control and BNG presented similar weight loss (-2.7% vs -3.9%, p=0.154). Total fat mass (%) was only reduced in the BNG compared to the baseline (Figure 2b). Women allocated to the BNG presented higher reductions in WC and WHtR compared to the control group, but without statistical significance (Table II and Figure 2a). At the same time, the truncal lean mass (%), android lean mass (%), truncal fat-free mass (%), and android fat-free mass (%) decreased more in the control group, compared to the BNG (Figure 2c and 2d). Moreover, total lean mass (%) and total fat-free mass (%) increased in the BNG compared to the baseline values (Figures 2c and 2d). Hip circumference, android FM, and gynoid FM (kg) were higher in the control group compared to the BNG at baseline, but all other variables were similar between groups (Table II).

Figure 2
Schematic of study design.

Results of cardiometabolic markers

The biochemical variables presented in this study did not differ between groups at baseline (Table III). Insulin and HOMA-IR decreased while Apo A1 increased in the BNG compared to baseline. BN consumption led to a 27.4% mean increase in Apo A1 versus 6.3% in the control group (p-value ≤ 0.001). The Apo B/Apo A1 ratio increased in the BNG, but the final ratio was lower than the control group. On the other hand, total cholesterol, LDL-c, and non-HDL-c decreased in the control group compared to baseline. Regarding liver enzymes, AST, ALT, and GGT decreased only in the BNG compared to baseline, being the changes in GGT enzyme were higher in the BNG compared to the control group. Alkaline phosphatase and fatty liver index decreased in both groups, but the BNG showed a greater reduction in alkaline phosphatase than the control group (Table III).

Table III
Change in selenium and cardiometabolic markers, according to 8-wk intervention (control vs. BNG).

	Control group (n=24)		BNG (n=25)		Baseline p-value	∆ p-value
	Baseline	∆	Baseline	∆
Serum selenium, µg/l	62.08 (30.34)	1.86 (40.98)	71.36 (27.10)	159.48 (85.98) **	0.269	<0.001
Fasting glucose, mg/dl	92.61 (11.45)	1.39 (8.38)	93.8 (11.51)	2.32 (8.75)	0.721	0.709
Insulin, μUI/ml	11.13 (4.32)	-0.94 (4.49)	13.07 (5.62)	-2.98 (4.27) *	0.189	0.114
HOMA-IR	2.54 (1.05)	-0.19 (1.14)	3.01 (1.27)	-0.60 (1.03) *	0.170	0.192
TyG index	8.44 (0.50)	0.01 (0.33)	8.44 (0.49)	0.15 (0.41)	0.991	0.217
TC, mg/dl	177.63 (32.78)	-6.42 (11.33) *	187.2 (38.14)	-4.28 (23.96)	0.352	0.690
LDL-c, mg/dl	101.29 (28.86)	-5.88 (8.57) *	113.04 (36.71)	-3.84 (22.54)	0.220	0.677
HDL-c, mg/dl	47.88 (12.79)	-0.13 (8.39)	52.48 (15.63)	-2.56 (7.87)	0.266	0.300
VLDL-c, mg/dl	22.69 (17.02)	0.85 (6.83)	21.68 (9.62)	2.12 (8.99)	0.798	0.581
Triglycerides, mg/dl	113.33 (85.15)	4.50 (34.17)	109 (47.99)	9.76 (44.58)	0.826	0.646
Non-HDL-c	107.08 (30.79)	-7.19 (10.01) *	112.92 (36.72)	-3.67 (22.48)	0.550	0.481
TC/HDL-c	3.86 (0.82)	-0.18 (0.58)	3.8 (1.16)	0.00 (0.45)	0.835	0.223
LDL-c/HDL-c	2.24 (0.80)	-0.18 (0.44)	2.35 (0.98)	-0.06 (0.47)	0.650	0.372
Apo E, mg/l	42.83 (17.03)	0.47 (7.74)	46.01 (11.87)	0.23 (8.28)	0.454	0.917
Apo B, mg/dl	84.91 (15.06)	-2.13 (6.41)	94.04 (28.99)	-2.48 (16.45)	0.175	0.922
Apo AI, mg/dl	127.87 (26.07)	7.09 (23.94)	140.2 (38.14)	37.48 (20.58) **	0.201	<0.001
Apo B / Apo AI	0.68 (0.16)	0.95 (0.18)	0.71 (0.25)	0.79 (0.14) **	0.719	0.001
AST, U/L	24.58 (5.69)	0.67 (24.86)	26.17 (7.57)	-9.05 (6.42) **	0.413	0.065
ALT, U/L	16.67 (5.31)	-0.21 (7.78)	18.85 (7.61)	-3.21 (4.33) **	0.252	0.106
GGT, U/L	23.17 (10.25)	-2.08 (6.17)	36.85 (33.59)	-9.69 (17.11) *	0.062	0.045
Alkaline phosphatase, U/L	75.13 (19.10)	-5.63 (7.75) *	83.36 (26.99)	-16.88 (13.82) **	0.225	0.001
FLI	75.49 (16.57)	-7.11 (12.06) *	70.98 (20.61)	-7.78 (12.53) *	0.410	0.852

• Values are mean (SD). Δ = final assessment – baseline. * p < 0.05 or ** p < 0.001 are significant differences within-group (paired t-test). Baseline p-values and Δ p-values refer to the comparison between groups (Student t test). BNG, brazil nut group; HOMA-IR, homeostatic model of insulin resistance assessment; TyG index, Triglyceride-glucose index; TC, total cholesterol; LDL-c, low-density lipoprotein cholesterol; HDL-c, high-density lipoprotein cholesterol; VLDL-c, very-low-density lipoprotein cholesterol; Apo AI, Apolipoprotein AI; Apo B, Apolipoprotein B; Apo E, Apolipoprotein E; AIP, atherogenic index of plasma; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-glutamyl transferase; FLI, fatty liver index.

Relationship between serum selenium and cardiometabolic risk markers

Approximately 86% of participants had low serum selenium (<100 µg/L) at baseline. After 8-wk intervention, the median of serum selenium increased 276.7% (95% CI: 199.4%-327.4%) in the BNG (p≤0.001) and 5.2 % (-7.7%-50,4%) in the control group. In the control group, 91.7% of the women remained with low serum selenium, while no women with low serum selenium were observed in the BNG.

To assess the potential relationship between the change in serum selenium and cardiometabolic risk markers, we divided the sample by the median change in serum selenium. Participants above the median of selenium variation had more preserved variations in LM and FFM of the trunk and android regions, at the same time that had more increase in APO A1 and lower means of Apo B/Apo A1 ratio and alkaline phosphatase compared to women under the median of serum selenium variations (Table SV).

DISCUSSION

In this study, an energy-restricted diet enriched with two units of BN resulted in similar weight loss to the control group in women with overweight/obesity, but it significantly preserved lean mass and fat-free mass of the truncal and android regions.

Studies with a similar intervention to our study (energy-restricted diet + nuts) were observed in the literature (Caldas et al. 2022, Rock et al. 2017, Abazarfard et al. 2014), but this is the first study that evaluated the consumption of BN without the combination of other nuts in the context of an energy restriction. In a 16-week randomized controlled clinical trial, consumption of 42 g/day of pistachios associated with a caloric deficit of 500 to 1000 kcal/day had no superior effects on weight reduction, BMI, waist circumference, and other cardiometabolic risk markers in adults with overweight/obesity (Rock et al. 2020). In another study, consumption of 56g of conventional or high-oleic peanuts associated with a caloric deficit of 250 kcal/day also did not have superior effects to nut-free energy restriction on anthropometric and body composition markers in men with overweight/obesity after four weeks of intervention (Alves et al. 2014). However, consumption of high oleic peanuts decreased total body fat (kg and %) and gynoid fat (%) while increasing gynoid and total lean mass (%) when compared to baseline. Interestingly, the group that received only energy restriction decreased total and trunk fat-free mass and total and trunk lean mass (kg) compared to baseline. On the other hand, consumption of 50g/day of almonds associated with 1000 kcal of caloric deficit reduced weight, BMI, waist circumference, waist-to-hip circumference ratio, markers of glucose and lipid metabolism, and diastolic blood pressure after 12-wk intervention compared to the nut-free group in women with overweight/obesity (Abazarfard et al. 2014). Different nuts, intervention time, and energy-restrictions were performed in these studies, which makes difficult comparisons. However, almonds have higher amounts of monounsaturated fatty acids, which may help explain the better results observed in the study (Abazarfard et al. 2014).

One of the explanations for the improvement in body composition in our study and others with a similar design but with other types of nuts is that, despite being foods rich in fat, nuts are not associated with weight gain (Natoli & McCoy 2007, Tan et al. 2014). Nuts is a food matrix, for unprocessed nuts, the vegetal cell wall restricts access to its lipid content, and therefore, not all the fat in the nuts is bioaccessible and much is lost in the feces (Cassady et al. 2009). Moreover, most of the fats in nuts are unsaturated and this fat profile is more rapidly oxidized and has a greater thermogenic effect than saturated fats, leading to less fat accumulation in the body (Casas-Agustench et al. 2009, Piers et al. 2002). Another hypothesis is that nuts affect satiety and thus reduce total energy intake (Natoli & McCoy 2007). Despite all these hypotheses, the consumption of unsaturated lipids was the same in the groups evaluated in our study. Furthermore, among the nutrients evaluated, selenium was the only one that increased after BN consumption compared to the control group.

Furthermore, we showed more pronounced preservation of lean and fat-free mass of the trunk and android region in women with higher median variation in serum selenium. These results suggest a new hypothesis for improving body composition after BN consumption through increasing serum selenium. However, the results of the studies still need to be clarified. Selenium is an essential precursor of selenoproteins, which are important in cellular redox homeostasis (da Silva et al. 2022, Silveira et al. 2020). Evidence suggests that selenium prevents adipogenesis by modulating selenoproteins gene expression and oxidative stress-related genes. The literature also indicates that both selenium deficiency and excess are harmful to health and may contribute to adipose tissue dysfunction and the consequent manifestation of metabolic alterations (Abo El-Magd et al. 2022, Tinkov et al. 2020). Indeed, selenium appears to participate in adipocyte hypertrophy and adipogenesis. Selenium in the physiological range possesses an overall adipogenic effect by activating the peroxisome proliferator-activated receptor and the CCAAT enhancer-binding protein-α (C/EBP) signaling through positive modulation of PI3K/Akt and C/EBP-β/δ pathways, resulting in up-regulation of adipocyte-specific genes. On the other hand, selenium overload exerts antiadipogenic activity through suppression of peroxisome proliferator-activated receptor and C/EBPα expression through several mechanisms including reduction of C/EBPβ expression as well as activation of 5’AMP-activated protein kinase and transforming growth factor β (Abo El-Magd et al. 2022, Tinkov et al. 2020). Thus, according to these mechanisms, we could justify the better body composition in women with greater variation in serum selenium after 8-wk nutritional intervention.

We also observed a higher increase in serum selenium and apolipoprotein A parallel to a decrease in liver enzymes and a lower Apo B/Apo A1 ratio in BNG compared to control. Although many articles are found in the literature regarding the potential benefits of BN consumption (Cominetti et al. 2012, Strunz et al. 2008, Thomson et al. 2008, Stockler-Pinto et al. 2010, Cardoso et al. 2017), this is the first study to evaluate BN consumption in the context of an energy-restricted diet on cardiometabolic risk markers.

The increase in serum selenium after BN consumption is not new (Li et al. 2020, da Silva et al. 2022). All studies with BN that evaluated this mineral in the blood observed an increase (Godos et al. 2022), suggesting high absorption rate and bioavailability of selenium from these nuts. Unlike Apo B, which is the main apoprotein of atherogenic particles constituted by lipoproteins VLDL-c, IDL-c, and LDL-c, Apo A1 is the main apoprotein of HDL-c, which is antiatherogenic. Apo-A1 is also a cofactor of the Lecithin-Cholesterol Acyltransferase (LCAT) enzyme, which plays a role in cholesterol esterification (Faludi et al. 2017). A study of rats fed a high-fat diet and co-supplemented with selenium and magnesium showed a decrease in 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase and an increase in cholesterol 7α-hydroxylase (CYP7A1) and LCAT in the liver (Zhang et al. 2018). HMG-CoA reductase participates in the cholesterol biosynthesis pathway while LCAT removes cholesterol from blood and tissues (Faludi et al. 2017). In a study with hypercholesterolemic rats, selenium supplementation decreased Apo B and HMG-CoA reductase expression (Dhingra & Bansal 2006). These data suggest a potential protective role of selenium in modulating lipid metabolism. No human studies have been found to confirm these findings.

A systematic review and meta-analysis showed that consumption of nuts generally did not affect Apo A1 levels but decreased Apo B, total cholesterol, triglycerides, and LDL-c. In addition, strong effects were observed in the decrease of Apo B in subjects with type 2 diabetes (Del Gobbo et al. 2015). The profile of fats found in nuts, with a predominance of unsaturated fats, is one of the explanations for the beneficial effects observed in the consumption of nuts in the improvement of the lipid profile. Despite this, in our study, the profile of ingested fats did not differ between the groups evaluated. Selenium was the nutrient that differed between the groups and, therefore, may be associated with the effects observed in our study. In addition, we have to consider that despite having similar weight loss to the group that received an energy-restricted diet free of BN, the group that consumed BN presented a tendency to lost more waist circumference. The loss of weight and fat in the abdominal region can be linked to an improvement in the metabolic profile (Kiriyama et al. 2021).

Furthermore, we observed that the consumption of BN decreased more pronouncedly alkaline phosphatase and GGT compared to the control group. Although not different between the two groups, the FLI reduced in both groups after the intervention. The relationship between selenium and liver enzymes is not clear in the literature. In addition to being controversial, the studies are mostly with experimental models. The role of selenium also appears to depend on the amount in which it is present in the blood. In a cross-sectional study with subjects with a median plasma selenium concentration of 213.0 µg/L, high plasma selenium levels were associated with higher ALT, AST, GGT, and higher odds of nonalcoholic fatty liver disease (Yang et al. 2016). On the other hand, body selenium status and selenium intake were negatively associated with hepatitis, cirrhosis, and liver cancer in a meta-analysis (Lin et al. 2022). In a study with rats induced to liver damage by the hepatotoxic agent carbon tetrachloride, a decrease in the activity levels of AST, ALT, and GGT enzymes parallel to the increase in plasma alkaline phosphatase was observed after selenium injection (Ozardalı et al. 2004). In another study, rats exposed to toxic doses of heavy metals showed a decrease in serum alkaline phosphatase activity, which was not influenced by selenium supplementation (Şlencu et al. 2015).

The mechanisms behind the connection between selenium and decreased liver enzymes are unclear. What is known is that alkaline phosphatase is a hydrolase involved in dephosphorylation and that GGT participates in the γ-glutamyl cycle, a pathway of glutathione synthesis and degradation (Huber et al. 2008, Bachhawat & Yadav 2018). In turn, glutathione peroxidase is a type of glutathione involved in the enzymatic defense system against free radicals that incorporate a selenocysteine residue in its active site. Selenocysteine has a selenium atom in its structure, making it necessary to maintain selenium levels to form enzymatic antioxidant defense systems (Huber et al. 2008).

The main limitation of this study was the lack of randomization of participants between groups. Randomized controlled trials are at the top of the scientific evidence for conducting studies that investigate cause and effect. The non-randomization of the sample can lead to selection bias. Despite this, our study had a control group, and most variables did not differ between participants at baseline. We used appropriate statistics to correct the initial variability between groups for the variables that differed at baseline. Another limitation was that we added a sauce to the participants’ diets to balance the macro and micronutrient diets. To avoid exposure bias, both groups received the sauce. Furthermore, different percentages of losses were observed in both groups. Despite this, the characteristics of the participants who started the study regarding anthropometric, body composition and biochemical variables were similar at baseline compared to the participants who dropped out of the study. A strength of our study is the use of DEX, the gold standard method to evaluate body composition. Also, both physical activity and preparation for performing the DEX were monitored during the study. Finally, we believe presenting an innovative study, the first to assess the potential effects of BN consumption combined with an energy-restricted diet.

CONCLUSIONS

In conclusion, the consumption of 2 units/day of BN in an 8-week weight loss intervention preserved lean and fat-free mass in women with overweight or obesity. Additionally, BN consumption increased serum selenium and apolipoprotein A1 while decreased liver enzymes compared to an energy-restricted diet free of BN. These findings suggest that the consumption of BN in a dietary approach for obesity treatment may be a strategy to reduce central adiposity, preserve lean mass, improve antioxidant status, lipid, and liver function markers, and consequently, help in the management of obesity and its comorbidities. Studies investigating the molecular metabolic pathways behind the effects are encouraged.

SUPPLEMENTARY MATERIAL

Tables SI-SV.

Acknowledgements

We acknowledge all the women who voluntarily participated in the study and the ECONUT© (Excelsa Institute) for donating the Brazil nut used in this study.

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Publication Dates

• Publication in this collection
  14 Apr 2025
• Date of issue
  2025