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Revista chilena de nutrición

versión On-line ISSN 0717-7518

Rev. chil. nutr. vol.47 no.5 Santiago set. 2020

http://dx.doi.org/10.4067/s0717-75182020000500772 

Original Article

Dietary patterns of Brazilian adults with neurofibromatosis type 1

Patrones dietéticos de adultos brasileños con neurofibromatosis tipo 1

Darlene Larissa de Souza Vilela1  2 

Marcella Assis de Paula Costa e Souza1 

Ann Kristine Jansen1 

Nilton Alves de Rezende3 

Luiz Oswaldo Carneiro Rodrigues3 

Marcio Leandro Ribeiro de Souza1  3  * 

1Federal University of Minas Gerais, Nutrition Department, Belo Horizonte, Brazil.

2Federal University of Viçosa, Nutrition Department, Viçosa, Brazil.

3Federal University of Minas Gerais, Medicine School, Belo Horizonte, Brazil.

ABSTRACT

Neurofibromatosis type 1 (NF1) is an autosomal dominant genetic disease characterized by multisystem involvement such as bone, muscle, endocrine, ophthalmologic, cardiovascular, central and peripheral nervous system, cognitive capacity, voice, and oral motor disorders. Nutritional studies in individuals with NF1 have been performed recently. While a previous study showed an inadequate nutrient intake in patients with NF1, the dietary patterns of this population have not yet been widely studied. This study aimed to characterize dietary patterns in Brazilian adults with NF1. Sixty NF1 individuals (51.7% women), ≥18 years of age underwent nutritional assessment including laboratory analysis, anthropometrics, and eating habits recorded on a food frequency questionnaire. Cluster analysis was used to distinguish between dietary patterns. Hypothesis tests were used to compare data. Two groups with distinct patterns were identified, “Healthy” (46.7%) and “Western” (53.3%). These groups were similar in most of the socioeconomic, anthropometric, demographic and laboratory parameters evaluated. However, the upper-arm total area and upper-arm muscle area (UAMA) were lower in the Western group than those in the Healthy group [59.8 (25.7) cm2 versus 65.6 (28.3) cm2, P=0.049; 35.6±12.4 cm2 versus 43.8±15.0 cm2, P=0.024, respectively]. In this study, most individuals with NF1 had a Western dietary pattern and this group showed a lower UAMA, which may indicate a potential contribution, even in part, of diet in the muscle phenotype in this population. This association between diet and muscle in NF1 individuals requires investigation in further studies.

Keywords: Dietary patterns; Food intake; Neurofibromatosis type 1; Nutritional status; Skeletal muscle

RESUMEN

La neurofibromatosis tipo 1 (NF1) es una enfermedad genética autosómica dominante caracterizada por la afectación multisistémica, alterando los sistemas óseo, muscular, endocrino, oftálmico, cardiovascular, nervioso central y periférico así como las capacidades cognitivas. Un estudio previo señaló una ingesta inadecuada de nutrientes en pacientes con NF1, pero los patrones dietéticos de esta población aún no han sido estudiados ampliamente. El objetivo de este est udio es caracterizar los patrones dietéticos en brasileños con NF1. Sesenta individuos con NF1 (51,7% mujeres) ≥18 años se sometieron a una evaluación nutricional que incluyeron análisis de laboratorio, antropometría y hábitos alimentarios registrados en un cuestionario de frecuencia alimentaria. El análisis de conglomerados se utilizó para distinguir los patrones dietéticos; las pruebas de hipótesis para comparar datos. Se identificaron dos grupos con patrones distintos, denominados Saludables (46,7%) y Occidentales (53,3%). Estos grupos fueron similares en la mayoría de los parámetros socioeconómicos, antropométricos, demográficos y de laboratorio evaluados. Sin embargo, las áreas total braquial (ATB) y muscular braquial (AMB) fueron menores en el grupo occidental que en el grupo sano [59,8 (25,7) cm2 y 65,6 (28,3) cm2, P= 0,049; 35,6 ± 12,4 cm2 y 43,8 ± 15,0 cm2, P= 0,024, respectivamente]. En este estudio, la mayoría de las personas con NF1 habían consumido un patrón dietético occidental y este grupo presentó un AMB menor, lo que puede indicar una contribución potencial, incluso en parte, de la dieta en el fenotipo muscular en esta población. Esta asociación entre dieta y músculo en personas con NF1 requiere investigaciones en estudios adicionales.

Palabras clave: Estado nutricional; Ingesta de alimentos; Músculo esquelético; Neurofibromatosis tipo 1; Patrones dietéticos

INTRODUCTION

Neurofibromatoses are a group of three genetic diseases characterized by dermatological alterations and propensity to several neural tumors 1. The most frequent form is neurofibromatosis type 1 (NF1), with a prevalence of 1:3,000 live births2. NF1 is an autosomal dominant disorder resulting from mutations in NF1, which is located on chromosome 17 and characterized by a dysfunction in neurofibromin synthesis, a protein responsible for suppressing tumor growth3. The diagnostic criteria of NF1 were defined in 1978 by a National Institutes of Health (NIH) consensus and are based on clinical features such as cafe au lait spots, dermal and plexiform neurofibromas, Lisch nodules, axillary and/or inguinal freckling, and bone dysplasia4. However, as neurofibromin is expressed in multiple cell types, there may be multisystem involvement such as bone, muscle, endocrine, ophthalmologic, cardiovascular, central and peripheral nervous system, cognitive capacity, voice, and oral motor disorders5,6.

Recently, studies on the nutrition aspects in NF1 have begun to be performed. Studies prior to 2014 were limited to anthropometric evaluation of this population. The anthropometric characteristics most often found in NF1 individuals include a high prevalence of low weight, short stature, macrocrania, reduced muscle mass, and lower body mass index7,8,9. Vitamin D deficiency or insufficiency, low bone mineral density, reduced muscle strength, and intestinal constipation have also been described and may be associated with an inadequate diet6,10,11,12.

The first study to evaluate nutrient intake in NF1, based on three 24-hour recalls, suggested that this population consumes an inadequate diet with excessive fat and sodium and deficient fiber and micronutrient consumption, especially magnesium, calcium, vitamin D and pyridoxine13.

However, the evaluation of dietary patterns is more comprehensive than that of isolated nutrients or foods. Meals are composed of multiple foods, resulting in interaction and synergy between their various components, which can compromise the effects on the body. Isolated analyses may be inappropriate because they disregard the results of these interactions as modifications to the bioavailability of nutrients and the simultaneous effects of components whose properties cannot be attributed to a single factor14,15. Therefore, the World Health Organization (WHO) recommends the use of dietary patterns as an adequate method to indicate possible associations between diet, health and biopsychosocial aspects involved in the eating process16.

Thus, due to the scarcity of studies evaluating food consumption among individuals with NF1 and the lack of studies evaluating dietary pattern among individuals with NF1, this study aimed to characterize the dietary profile of this population and its relationship with anthropometric, sociodemographic and health characteristics.

METHODS

Study design and sample

This observational cross-sectional study included all individuals with a confirmed clinical diagnosis of NF1 according to NIH Consensus diagnostic criteria4, aged ≥18 years, of both sexes, who were evaluated between September 2012 and September 2013 in a Brazilian Neurofibromatosis Outpatient Reference Center. The exclusion criteria were musculoskeletal limitations in the upper and/or lower limbs, use of medications that could compromise nutritional assessment, cancer, or the presence of acute and cronic diseases that required specific diets or food intake.

The sample size was calculated based on the results of the study by Souza et al considering 54.9% of inadequate micronutrient consumption13 and a population of 464 adults in a Brazilian Neurofibromatosis Outpatient Reference Center at that time. A power calculation was performed using Epi Info™®. To attain 90% power, a minimum of 59 individuals was required.

Data collection and instruments

A trained registered dietitian performed all data collection. This procedure was adopted in order to avoid bias such as discrepancies between evaluators in anthropometric measurement as well as induction and/or value judgments that could compromise the assertiveness of the responses during the application of the food frequency questionnaire (FFQ).

For sample characterization, information on sociodemographic and health was collected, including age, per capita household income, and physical activity. Individuals with NF1 were asked about the periodicity of each food's consumption in the six months preceding the interview, with the following options: daily, weekly, monthly, or never consumed. Data on food intake were obtained by means of a semi-quantitative FFQ containing 67 food items. The FFQ was developed and validated by Ribeiro and Cardoso17 by adaptating of a validated questionnaire applied to the Japanese-Brazilian community18, excluding foods of Japanese origin. This FFQ was validated for nutritional assessment and actions to prevent non-communicable chronic disease17. Items commonly consumed in the county (cheese brea and cassava starch snacks) were included in our study. As our objective was to qualitatively evaluate dietary patterns of individuals with NF1, only results related to habitual food frequencies of consumption have been presented.

Physical activity level was evaluated using the validated International Physical Activity Questionnaire (IPAQ) short version. Physical activity levels were classified as very light, light, moderate or heavy according to the IPAQ19.

Laboratory test results were also included in this study. Blood levels of glycemia, total cholesterol and fractions, and triglycerides were measured at the hospital's clinical analysis laboratory after the individuals had fasted for 10–12 hours.

For anthropometry data, weight, height, waist circumference (WC), upper-arm circumference (UAC), and triceps skinfold thickness (TSF) measurements followed the protocol described by the WHO20.

Weight was measured using a mechanical scale (Welmy®) with sensitivity of 100g which was checked over and manually calibrated before each weighing. Height was measured with the vertical stadiometer of the scale (Welmy®). Weight and height were used to calculate body mass index (BMI). BMI categories included normal (BMI between 18.5 and 24.9 kg/m2), low (BMI <18.5 kg/m2), and overweight (BMI ≥ 25.0 kg/m2)20.

WC was measured at the midpoint between the iliac crest and the last rib. According to the WHO cutoff points, the maximum normal values for WC were 94 cm for men and 80 cm for women21.

UAC was measured using graduated tape at the midpoint between the acromion and the olecranon on the right side of all patients. Tricep skinfold (TSF) was measured at the same location marked for UAC, using a Cescorf® adipometer positioned perpendicular to the fold, with arms relaxed and extended along the body. The folds were measured vertically, 1 cm from the evaluator's left thumb and forefinger. Measurements were performed in triplicate and means were considered20.

TSF and UAC were used to calculate total upper-arm total area (UATA), upper-arm muscle area (UAMA), and upper-arm fat area (UAFA), using the following equations, according to Frisancho22 (π= 3.14):

UATA(cm2)=(UAC)2/(4×π)UAMA(cm2)={(UAC-TSF×π)2/(4×π)}10MenUAMA(cm2)={(UAC-TSF×π)2/(4×π)}6.5WomenUAFA(cm2)= UATAUAMA

Statistical Analyses

Data were recorded in a double typing process and later compared to evaluate consistency. All statistical analyses were performed using the STATA Version 14.0 software (STATA; Corp, College Station, Texas).

The food items on the FFQ were grouped into 23 categories according to the similarities of nutritional content and culinary use. The frequencies of consumption of these foods were transformed into a daily consumption score. Dietary patterns were identified via cluster analysis and the variables were initially standardized (with mean zero and standard deviation one). The squared Euclidean distance was adopted as a criterion for dissimilarity; the Ward method was applied for conglomerate formation and the determination of group numbers was performed a posteriori using the Pseudo T2 statistic23. For interpreting this analysis, the mean of the standardized scores was used; in other words, frequencies of consumption below or above the average were considered negative and positive factors, respectively. In our study, two dietary patterns were identified, Healthy and Western, considering the foods most consumed by individuals in each group.

Grouped comparisons of qualitative variables were performed using Fisher's chi-square or exact tests. Qualitative variables were described as absolute and relative frequencies (percentage). Shapiro–Wilk tests were used for continuous variables to analyze their normality and to determine the appropriate statistical test. Normally distributed quantitative variables were described as means and standard deviation (SD). The groups were compared through independent-samples t-tests. Quantitative variables that were not normally distributed were presented as medians and interquartile range (IQR) and were compared by Mann–Whitney U tests. Multiple linear regression analyses were performed to adjust the variables that showed a statistically significant difference between the groups to the confounding factors. P-values <0.05 were considered statistically significant.

Ethical Statement

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Ethics Committee of the Federal University of Minas Gerais (#81497). Written informed consent was obtained from all subjects.

RESULTS

This study included 60 individuals with NF1 aged 18-64 years (51.7% women). Two groups with different dietary patterns were identified: Western and Healthy. Figure 1 shows the comparisons of consumption between the two patterns based on standardized mean scores from the cluster analyses.

Figure 1 Comparison of consumption between Western and Healthy patterns based on cluster analyses. 

The first pattern, termed Western, contained 32 individuals (53.3%) and was characterized by a frequency of consumption above the average of margarine and mayonnaise, pastry and fried foods, sausages, artificial and alcoholic beverages. The second pattern, termed Healthy, included 28 individuals (46.7%) and was characterized by an increased frequency of consumption compared to the average of fruits, vegetables, legumes, nuts, natural drinks (coffee, tea, and fresh fruit juices), white meat, and seafood. Table 1 presents the food distributions for each dietary pattern based on cluster analysis.

Table 1 Food distributions for each dietary pattern in individuals with NF1 based on cluster analysis. 

FOOD Pattern 1 Western (n= 32) Pattern 2 Healthy (n= 28)
Mean SD Mean SD
Dairy products -0.054 (1.008) 0.061 (1.006)
White meats and seafood -0.363 (0.554) 0.415 (1.224)
Low-fat red meat 0.407 (1.120) -0.465 (0.570)
High-fat red meat -0.224 (0.762) 0.256 (1.179)
Viscera -0.115 (0.643) 0.131 (1.295)
Sausages 0.157 (1.158) -0.179 (0.764)
Eggs 0.049 (1.259) -0.056 (0.600)
Breads and breakfast cereals 0.152 (1.126) -0.173 (0.820)
Pasta -0.127 (0.834) 0.145 (1.160)
Tubers and cereals 0.146 (1.171) -0.166 (0.746)
Fruit -0.435 (0.389) 0.498 (1.237)
Fresh fruit juices -0.367 (0.511) 0.419 (1.242)
Legumes -0.421 (0.988) 0.481 (0.784)
Leafy vegetables -0.289 (0.783) 0.330 (1.127)
Non-leafy vegetables -0.364 (0.689) 0.416 (1.141)
Nuts -0.343 (0.200) 0.392 (1.356)
Margarines and mayonnaise 0.314 (1.035) -0.358 (0.839)
Fats of animal origin -0.178 (0.954) 0.203 (1.030)
Pastry and fried foods 0.253 (1.116) -0.290 (0.769)
Sweets -0.023 (0.875) 0.026 (1.142)
Artificial beverages 0.215 (1.020) -0.246 (0.935)
Coffee and tea -0.154 (0.887) 0.176 (1.105)
Alcoholic beverages 0.012 (1.103) -0.014 (0.888)

Note: Values are expressed as the means and standard deviation (SD) of the standardized frequency scores of the food groups' consumption. Positive factors with consumption frequencies higher than the general average are bolded (cluster analysis).

Table 2 shows the demographic and socioeconomic characteristics of this study and the comparisons between the dietary patterns. There were no statistically significant differences in age, sex, per capita income, and education level between groups.

Table 2 Demographic and socioeconomic parameters in NF1 individuals comparing Western and Healthy dietary patterns. 

PARAMETERS All Western Healthy P-value
(n= 60) (n= 32) (n= 28)
Age (y), median (IQR) 34.0 (13.0) 30.5 (10.0) 35.0 (13.5) 0.070*
Sex, n (%) 0.448
Male 29 (48.3) 14 (43.8) 15 (53.6)
Female 31 (51.7) 18 (56.2) 13 (46.4)
Education level, n (%) 0.650
No education or incomplete primary school 10 (16.6) 4 (12.5) 6 (21.4)
Primary school 7 (11.7) 4 (12.5) 3 (10.7)
High school or above 43 (71.7) 24 (75.0) 19 (67.9)
Per capita income, n (%) 0.176
<= 1 BMW 29 (48.3) 14 (43.8) 15 (53.6)
1–3 BMW 29 (48.3) 18 (56.2) 11 (39.3)
> 3 BMW 2 (3.4) 0 2 (7.1)

Note: BMW: Brazilian minimum wage (considering U$175.00 or R$678.00 in 2013); IQR: interquartile range;

*Mann-Whitney U test;

Fisher's exact test and chi-square test.

No differences were observed in relation to the laboratory test data and the results were all within the laboratory reference range of values (Table 3). Regarding physical activity, individuals were mostly sedentary, forty-seven (78.3%) did not perform regular physical activity or performed only light daily activities, with no differences between groups regarding physical activity level (P= 0.753) (Table 4).

Table 3 Laboratory tests of individuals with NF1 comparing Western and Healthy dietary patterns. 

PARAMETERS All Western Healthy P-value
(n= 54) (n= 28) (n= 26)
Fasting blood glycaemia, median (IQR) 82.0 (9.0) 82.0 (8.5) 82.5 (12.0) 0.211*
Total cholesterol, mean (SD) 189.3 (6.4) 185.2 (9.6) 193.7 (8.6) 0.518
LDL, median (IQR) 103.3 (58.0) 99.4 (47.7) 116.9 (57.0) 0.299*
HDL, median (IQR) 53.0 (20.0) 52.5 (25.0) 53.0 (21.0) 0.521*
Triglycerides, median (IQR) 77.0 (44.0) 64.5 (34.5) 84.0 (51.0) 0.065*

Note: HDL: high-density lipoprotein; IQR: interquartile range; LDL: low-density lipoprotein; SD: standard deviation;

*Mann-Whitney U test;

Student's independent-sample t-test.

Table 4 Anthropometric and health parameters in NF1 individuals with Western or Healthy dietary patterns. 

PARAMETERS All Western Healthy P-value
(n= 60) (n= 32) (n= 28)
Weight (kg), median (IQR) 59.0 (20.5) 58.5 (21.0) 59.2 (16.4) 0.432*
Height (m), mean (SD) 1.62 (0.10) 1.64 (0.11) 1.61 (0.09) 0.281
BMI (kg/m2) median (IQR) 22.9 (5.7) 22.0 (5.3) 23.8 (5.8) 0.100*
WC (cm), median (IQR) 79.2 (21.3) 73.2 (19.0) 80.4 (17.9) 0.118*
UAC (cm), mean (SD) 28.3 (4.5) 27.4 (4.6) 29.4 (4.1) 0.094
TSF (mm), median (IQR) 12.0 (9.0) 11.5 (12.5) 12.0 (6.5) 0.888*
UATA (cm2), median (IQR) 61.5 (29.7) 59.8 (25.7) 65.6 (28.3) 0.049*
UAFA (cm2), median (IQR) 23.4 (10.2) 23.0 (14.2) 24.7 (7.0) 0.266*
UAMA (cm2), mean (SD) 39.4 (14.2) 35.6 (12.4) 43.8 (15.0) 0.024
BMI category – n (%) 0.208
Normal weight 35 (58.3) 19 (59.4) 16 (57.1)
Overweight 19 (31.7) 8 (25.0) 11 (39.3)
Low weight 6 (10.0) 5 (15.6) 1 (3.6)
WC category – n (%) 0.353
Normal 43 (71.7) 23 (71.9) 20 (71.4)
High risk 12 (20.0) 5 (15.6) 7 (25.0)
Very high risk 5 (8.3) 4 (12.5) 1 (3.6)
Physical activity level – n (%) 0.753
Very light 47 (78.3) 24 (75.0) 23 (82.1)
Mild to moderate 7 (11.7) 4 (12.5) 3 (10.7)
Active to very active 6 (10.0) 4 (12.5) 2 (7.2)

Note: BMI: body mass index; IQR: interquartile range; SD: standard deviation; UAC: upper-arm circumference; UAFA: upper-arm fat area; UAMA: upper-arm muscle area; UATA: upper-arm total area; TSF: triceps skinfold; WC: waist circumference;

Student's independent-sample t-test;

*Mann-Whitney U test;

chi-square test.

Regarding BMI categorization, the Western pattern included 19 (59.4%) individuals classified as normal weight, while eight (25.0%) were overweight and five (15.6%) were underweight. The Healthy pattern had 16 (57.1%) with normal weight, 11 (39.3%) overweight and one (3.6%) underweight person. There was no statistically significant difference between the groups (P= 0.208) (Table 4).

Both groups were similar in relation to anthropometric parameters, except for UATA and UAMA (Table 4). The UATA was significantly higher in the Healthy group compared to the Western group (P= 0.049). The UAMA was also higher in the Healthy group compared to the Western group (P= 0.024). The UAFA did not differ significantly between groups (P= 0.264) (Table 4). Multiple linear regression analyses were performed to test whether there was any difference in the UAMA between the dietary patterns, after adjusting for sex, age, BMI and physical activity level, with the Healthy pattern considered the referent group. The association between dietary pattern and UAMA remained significant even after adjustments. Adherence to the Western dietary pattern reduced UAMA by 4 cm2 regardless of the factors mentioned above (P= 0.018) [CI 95% -7286035 – -.71864] (Table 5).

Table 5 Factors related to UAMA, mutiple linear regression adjusting for confounding factors. 

UAMA (cm2) Coefficient p>|t| [95% C.I.]
Dietary Pattern (ref= Healthy) -4.002.338 0.018 -7286035 -.71864
Sex 1.150.208 <0.001 827.512 1.472.904
Age* .0078604 0.921 -.1500877 .1658085
BMI* 2.084.817 <0.001 1.740.716 2.428.918
Physical Activity Level -6.979.846 0.223 -18.32855 4.368.862

*The categories are shown in table 4. Note: BMI: body mass index; CI: confidence interval; UAMA: upper-arm muscle area.

DISCUSSION

The results of this study demonstrated two different dietary patterns, Healthy and Western, among individuals with NF1. Individuals with the Western pattern had a lower UAMA than the Healthy pattern group, suggesting a potential contribution of this dietary pattern on muscular aspects of NF1.

In general, balanced diets that are based on fresh and minimally processed foods, mainly fruit and vegetables, are considered Healthy patterns, which correspond to the recommendations of the Dietary Guidelines for the Brazilian Population24. In contrast, the Western pattern was based on energy-dense, low-nutrient-density foods, rich in ultra-processed foods and artificial beverages, and had reduced consumption of fresh foods such as fruit and vegetables. The food consumption by the Western group in our study is similar to that of the dietary pattern of the general Brazilian population24,25,26.

Consumption of a Western Diet can contribute to the low fiber and micronutrient content, as well as to the excessive consumption of fat and sugars and high-energy density foods27. Although this study did not evaluate quantitative data, our results are consistent with those of a study of nutrient intake performed previously by our research group, in which NF1 individuals had an unhealthy diet characterized by excessive saturated fat and a deficiency of vitamins, minerals and fiber13. An unhealthy diet might affect the severity of the clinical manifestations of some comorbidities among NF1 individuals, such as constipation, bone alterations, and reduced muscle mass13. An inadequate diet may also predispose individuals to increased risks of chronic diseases such as cancer and cardiovascular disease, whose prevalence is high in NF1 individuals28,29.

Currently, there is no effective therapy for the growth of neurofibromas and, perhaps, diet can contribute to the control of clinical characteristics of NF1, which needs to be studied in future studies13. For example, the study of Esposito et al30 conducted with a small and uncontrolled sample, reported that adherence to a curcumin-enriched Mediterranean diet in individuals with NF1 was associated with improvement in nutritional and metabolic parameters and reduction in the number and volume of cutaneous neurofibromas.

In our study, individuals with the Healthy pattern had higher UAMA when compared to that in the Western pattern group. There were no differences in age and physical activity level between the groups. The NF1 population usually presents musculoskeletal disorders, including reduced crosssectional muscle area, lower muscle strength, and poor motor coordination7,8,31. Reduced muscle mass and strength may be present since childhood and can compromise the quality of life of this population32. Studies in individuals without NF1, especially in the elderly, have shown that healthy eating patterns can positively influence muscle mass. Healthy eating patterns are positively associated with lower limb strength33 and inversely associated with sarcopenia34. In contrast, the high-fat Western Diet may impair muscle metabolism, as it produces increased levels of inflammatory cytokines such as interleukin-1 (IL-1) and decreased levels of insulin-like growt factor-1 (IGF-1), leading to subsequent muscle damage, which may produce muscle hypotrophy and reduced strength35. The association between diet and muscle in NF1 requires further investigation.

Individuals with NF1 often have cardiovascular disease, which causes about 16–18% of mortality29. Adherence to a Western dietart pattern increases the risk of cardiovascular disease compared to that in other patterns, likely due to its association with increased inflammation and cardiovascular disease progression36,37. Inflammation is also associated with the number of neurofibromas in NF1 patients38, although the impact of diet on inflammation in NF1 has not been investigated. Despite approaching the recommendations of the Dietary Guidelines for the Brazilian Population24, the Healthy pattern in our study showed consumption of some dietary sources of saturated fats, usually classified as a risk factor for cardiovascular diseases. However, it is important to note that our data indicate only consumption; therefore, it is not possible to determine quantities of foods consumed.

Individuals with NF1 are at higher risk of cancer development compared to the general population39. Malignant peripheral nerve sheath tumors are the main cause of death in this population40. The Western dietary pattern has been linked to an increased risk of cancer, increased obesity, oxidative damage, and reduced antioxidant defense41,42,43,44.

The Western pattern is likely influenced by the local food environment, since the Brazilian population went through a process of replacing the consumption of basic and traditional foods with ultra-processed foods between 1974 and 2003, which resulted in increased consumptions of total and saturated fats, maintenance of the excessive intake of sugar, and deficient fruit and vegetable consumption45. In addition, there is evidence that income and education level can influence dietary patterns and food purchases, in which higher income and education favor healthier food choices46. In our study, income level and education were similar between groups.

Adherence to the Healthy pattern, observed in 46.7% of the sample, contrasted with the pattern observed in the general Brazilian population and may be related to uncertainty about disease progression and absence of a cure. Until now, there is no scientific evidence for any effect of diet on NF1. There is also no specific treatment that prevents the growth of neurofibromas. Thus, some individuals with NF1 may have food choice concerns, leading them to seek a healthy diet in an attempt to reduce the risk of developing comorbidities or to induce neurofibromas reduction or even attenuate their growth. It is important to report that none of the individuals in our study had prior nutritional monitoring.

This study had limitations regarding the sample and the methods. Non-probabilistic sampling was performed, given the specificity of the population and the disease, and there was no control group. The FFQ method also has limits due to the improper grouping of foods, an incomplete food list, and the reliance on individual memory for the self-reported frequencies. However, to avoid this kind of bias, a validated questionnaire was used and the interviewer was trained to apply this tool. In addition, UAMA is not the best method for assessing muscle mass; future studies should use gold standard parameters to investigate muscle mass in individuals with NF1. Despite these limitations, this study demonstrated differences in the dietary patterns of individuals with NF1, which indicates that nutritional interventions may be an option to improve the quality of life of this population.

In conclusion, most individuals with NF1 in this study had a Western dietary pattern of food consumption. Our results also demonstrated a relationship between the Healthy dietary pattern and greater upper-arm muscle area, suggesting a nutritional potential contribution, in part, to the muscle impairment commonly described in NF1. Further studies should investigate the mechanisms of action of this association as well as the impact of nutrition and diet on clinical characteristics in individuals with NF1. The high prevalence of individuals in the Western pattern group reinforces the importance of nutritional interventions in this population.

Funding:

This work was supported by CAPES; National Council of Technological and Scientific Development-CNPq (#471725/2013-7); FAPEMIG (#APQ-00928-11; #PPM-00120-14). The funding sources played no role in the study design and analysis or in the writing of the manuscript or decision to publish.

REFERENCES

1. Rodrigues LOC, Batista PB, Goloni-Bertollo EM, Souza-Costa D, Eliam L, Eliam M et al. Neurofibromatoses: part 1 – diagnosis and differential diagnosis. Arq Neuropsiquiatr 2014; 72: 241-250. [ Links ]

2. Friedman JM. Epidemiology of neurofibromatosis type 1. Am J Med Genet 1999; 89: 1-6. [ Links ]

3. Jett K, Friedman JM. Clinical and genetic aspects of neurofibromatosis 1. Genet Med 2010; 12: 1-11. [ Links ]

4. Neurofibromatosis, (N.I.H) Conference statement. National Institutes of Health consensus development conference. Arch. Neurol 1988; 45: 575-578. [ Links ]

5. Ruggieri M, Huson SM. The neurofibromatoses. An overview. Ital J Neurol Sci 1999; 20: 89-108. [ Links ]

6. Souza JF, Toledo LL, Ferreira MCM, Rodrigues LOC, Rezende NA. Neurofibromatosis type 1: more frequent and severe then usually thought. Rev Assoc Med Bras 2009; 55: 394-399. [ Links ]

7. Souza MLR, Jansen AK, Martins AS, Rodrigues LOC, Rezende NA. Body composition in adults with neurofibromatosis type 1. Rev Assoc Med Bras 2016; 62: 831-836. [ Links ]

8. Summers MA, Quinlan KG, Payne JM, Little DG, North KN, Schindeler A. Skeletal muscle and motor deficits in neurofibromatosis type 1. J Musculoskelet Neuronal Interac 2015; 15: 161-170. [ Links ]

9. Koga M, Yoshida Y, Imafuku S. Nutritional, muscular and metabolic characteristics in patients with neurofibromatosis type 1. J Dermatol 2016; 43: 799-803. [ Links ]

10. Stevenson DA, Viskochil DH, Carey JC, Sheng X, Murray M, Moyer-Mileur L et al. Pediatric 25-hydroxyvitamin D concentrations in neurofibromatosis type 1. J Pediatr Endocrinol Metab 2011; 24: 169-174. [ Links ]

11. Petramala L, Giustini S, Zinnamosca L, Marinelli C, Colangelo L, Cilenti G et al. Bone mineral metabolism in patients with neurofibromatosis type 1 (von Recklingausen disease). Arch Dermatol Res 2012; 304: 325-331. [ Links ]

12. Ejerskov C, Krogh K, Ostergaard AJR. Gastrointestinal symptoms in children and adolescents with neurofibromatosis type 1. J Pediatr Gastroenterol Nutr 2018; 66: 872-875. [ Links ]

13. Souza MLR, Jansen AK, Martins AS, Rodrigues LOC, Rezende NA. Nutrient intake in neurofibromatosis type 1: A cross-sectional study. Nutrition 2015; 31: 858-862. [ Links ]

14. National Research Council. Diet and Health: implications for reducing chronic disease risk. National Academies Press, 1989. [ Links ]

15. Jacques PF, Tucker KL. Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr 2001; 73: 1-2. [ Links ]

16. FAO, World Health Organization Preparation and use of food-based dietary guidelines. Joint WHO/FAO Expert Consultation. WHO Technical Report Series nº 880. Geneva: WHO, 1998. [ Links ]

17. Ribeiro AB, Cardoso MA. Development of a food frequency questionnaire as a tool for programs of chronic diseases. Rev Nutr 2002; 15: 239-245. [ Links ]

18. Cardoso MA, Stocco PR. Development of a dietary assessment method for people of Japanese descent living in Sao Paulo, Brazil. Cad Saude Publica 2000; 16: 107-114. [ Links ]

19. Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE et al. International Physical Activity Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003; 35: 1381-1395. [ Links ]

20. World Health Organization. Physical Status: The Use and Interpretation of Anthropometry. Report of a WHO Expert Committee. WHO Technical Report Series 1995; (854): 452. Geneva: WHO, 1995. [ Links ]

21. World Health Organization. Waist Circumference and Waist-Hip Ratio: Report of a WHO Expert Consultation 2011; (64): 8-11. Geneva: WHO, 2011. [ Links ]

22. Frisancho AR. Anthropometric standards for the assessments of growth and nutritional status. University of Michigan Press, 1990. [ Links ]

23. Calinski T, Harabasz J. A dendrite method for cluster analysis. Commun Stat Theory Methods 1974; 3: 1-27. [ Links ]

24. Brasil. Ministério da Saúde. Dietary Guidelines for the Brazilian population 2nd ed. Brasilia, 2014. [ Links ]

25. Martins APB, Levy RB, Claro RM, Moubarac JC, Monteiro CA. Increased comtribution of ultra-processed food products in the Brazilian diet (1987-2009). Rev Saude Publica 2013; 47: 656-665. [ Links ]

26. Souza AM, Pereira RA, Yokoo EM, Levy RB, Sichieri R. Most consumed foods in Brazil: National Dietary Survey 2008-2009. Rev Saude Publica 2013; 47: 190S-199S. [ Links ]

27. World Health Organization. Diet, Nutrition, and the Prevention of Chronic Diseases: Joint WHO/FAO Expert Consultation. WHO Technical Report Series. Geneva, 2003. [ Links ]

28. World Health Organization. Global action plan for the prevention and control of non communicable diseases 2013-2020. Geneva, 2013. [ Links ]

29. Masocco M, Kodra Y, Vichi M, Conti S, Kanieff M, Pace M et al. Mortality associated with neurofibromatosis type 1: a study based on Italian death certificates (1995-2006). Orphanet J Rare Dis 2011; 6: 11-20. [ Links ]

30. Esposito T, Schettino C, Polverino P, Allocca S, Adelfi L, D'Amico A et al. Synergistic interplay between curcumin and polyphenol-rich foods in the Mediterranean diet: therapeutic prospects for neurofibromatosis 1 patients. Nutrients 2017; 9: 783-799. [ Links ]

31. Stevenson D, Moyer-Mileur LJ, Carey JC, Quick, JL, Hoff CJ, Viskochil DH. Case-control study of the muscular compartments and osseous strength in neurofibromatosis type 1 using peripheral quantitative computed tomography. J Musculoskelet Neuronal Interact 2005; 5: 145-149. [ Links ]

32. Cornett KMD, North KN, Rose KJ, Burns J. Muscle weakness in children with neurofibromatosis type 1. Dev Med Child Neurol 2015; 57: 733-736. [ Links ]

33. Wu F, Wills K, Laslett LL, Oldenburg B, Jones G, Winzenberg T. Associations of dietary patterns with bone mass, muscle strength and balance in a cohort of Australian middle-aged women. Br J Nutr 2017; 118: 598-606. [ Links ]

34. Kim J, Lee Y, Kye S, Chung YS, Kim KM. Association of vegetables and fruits consumption with sarcopenia in older adults: the Fourth Korea National Health and Nutrition Examination Survey. Age Ageing 2015; 44: 96-102. [ Links ]

35. Trovato FM, Castrogiovanni P, Szychlinska MA, Purrello F, Musumeci G. Impact of Western and Mediterranean diets and vitamin D on muscle fibers of sedentary rats. Nutrients 2018; 10: 231-245. [ Links ]

36. Katz DL, Meller S. Can we say what diet is best for health? Annu Rev Public Health 2014; 35: 83–103. [ Links ]

37. Samir P, Malireddi RKS, Kanneganti T. Food for training – Western diet and inflammatory memory. Cell Metab 2018; 27: 481-482. [ Links ]

38. Liao CP, Booker RC, Brosseau JP, Chen Z, Mo J, Tchegnon E et al. Contributions of inflammation and tumor microenvironment to neurofibroma tumorigenesis. J Clin Invest 2018; 128: 2848-2861. [ Links ]

39. Walker L, Thompson D, Easton D, Ponder B, Ponder M, Frayling I et al. A prospective study of neurofibromatosis type 1 cancer incidence in the UK. Br J Cancer 2006; 95: 233-238. [ Links ]

40. Evans DGR, O'Hara C, Wilding A, Ingham SL, Howard E, Dawson J et al. Mortality in neurofibromatosis 1 in North West England: an assessment of actuarial survival in a region of the UK since 1989. Eur J Hum Genet 2011; 19: 1187-1191. [ Links ]

41. Fabiani R, Minelli L, Bertarelli G, Bacci S. Western dietary pattern increases prostate cancer risk: a systematic review and meta-analysis. Nutrients 2016; 8: 626-641. [ Links ]

42. Castelló A, Amiano P, Larrea NF, Martin V, Alonso MH, Castano-Vinyals G et al. Low adherence to the western and high adherence to the Mediterranean dietary patterns could prevent colorectal cancer. Eur J Nutr 2019; 58: 1495-1505. [ Links ]

43. Senger DR, Li D, Jaminet S, Cao S. Activation of the Nrf2 cell defense pathway by ancient foods: disease prevention by important molecules and microbes lost from the modern Western diet. PLoS One 2016; 11: e0148042. [ Links ]

44. Ricceri F, Giraudo MT, Fasanelli F, Milanese D, Sciannameo V, Fiorini L et al. Diet and endometrial cancer: a focus on the role of fruit and vegetable intake, Mediterranean diet and dietary inflammatory index in the endometrial cancer risk. BMC Cancer 2017; 17: 757-763. [ Links ]

45. Levy-Costa RB, Sichieri R, Pontes NS, Monteiro CA. Household food availability in Brazil: distribution and trends (1974-2003). Rev Saude Publica 2005; 39: 530-540. [ Links ]

46. Deshmukh-Taskar P, Nicklas TA, Yang SJ, Berenson GS. Does socioeconomic, food group consumption vary by differences in demographic, and lifestyle factors in young adult? The Bogalusa Heart Study. J Am Diet Assoc 2007; 107: 223-234. [ Links ]

Received: April 15, 2020; Revised: May 29, 2020; Accepted: June 14, 2020

*Corresponding Author: Marcio Leandro Ribeiro de Souza, Federal University of Minas Gerais, Rua dos Guajajaras, 1470 / 1702, Belo Horizonte, MG, Brazil. CEP 30180-101. E-mail: marcionutricionista@yahoo.com.br

Conflict of Interest: The authors declare no conflicts of interest.

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