Undernutrition and Clinical Deterioration in Children with Cystic Fibrosis: Findings from a Prospective Study

Abstract

Cystic Fibrosis is a genetic disease that causes dysfunctions in the transmembrane chloride conductance regulatory protein in epithelial cells. The main manifestations are persistent pulmonary symptoms and low weight gain. Therefore, nutrition plays an essential role in the survival and quality of life of these patients. This study aimed to evaluate the influence of nutritional status on the clinical condition and life expectancy in Cystic Fibrosis pediatric patients. Prospective cohort study evaluating sociodemographic, birth, clinical, anthropometric data, food intake, Shwachman-Kulczycki score and lung function. A total of 102 patients were evaluated in the first stage and 88 patients at the end of the study. Relative risk (RR) and confidence interval (95% CI) were calculated, considering p<0.05 as significant. Patients who were in the <50th percentile presented cystic fibrosis related symptoms earlier (0.96±3.45 months vs. 5.08±17.73 months), 53.2% had gastroesophageal reflux disease, 70% depletion of muscle tissue and lower weight (22.19±13.34 vs. 23.27±14.80) compared to those who had a good nutritional status. Impaired nutritional status was associated with earlier onset of the disease symptoms, gastroesophageal reflux disease, muscle tissue depletion and low body weight, but not with other clinical variables in children and adolescents with cystic fibrosis.

Key words
Adolescent health; Child health; Cystic fibrosis; Nutritional status

INTRODUCTION

Cystic fibrosis (CF) is an autosomal recessive inherited genetic disease characterized by changes in the secretions of exocrine glands. It is a chronic and progressive condition that affects multiple body systems and results from mutations in the gene that encodes the cystic fibrosis transmembrane conductance regulator (CFTR) protein (CFF 2022a, Callebaut et al. 2017).

CF is a rare disease. It is estimated that there are 70 thousand people with the disease in the world. It occurs more frequently in Europe, North America and Australia, and the prevalence is lower in East Asia and Africa (Mota et al. 2015). According to the latest Brazilian CF Registry, 5.773 patients are registered, of which 73.51% are under 18 years of age (GBFC 2021). In Brazil, the incidence of the disease is 1:10,000 live births; however, there are differences between regions and according to the degrees of local miscegenation. The South region, for example, exhibits data which are similar to those of the European population, i.e. 1:2500 (Althanazio et al. 2017).

Nutritional status directly influences the clinical course and quality of life of patients with cystic fibrosis (CF), with malnutrition being one of the main challenges in treatment (Sullivan & Mascarenhas 2017). Patients with CF have higher energy expenditure at rest, aggravated by pulmonary complications, malabsorption and lower food intake due to inflammation, which increases the risk of malnutrition (Calella et al. 2018).

Adequate caloric intake is essential to maintain good nutritional status, associated with better lung function, fewer hospitalizations and infections, as well as longer survival and adequate growth (Del Ciampo et al. 2015, Sullivan & Mascarenhas 2017).

In cystic fibrosis (CF), malnutrition and declining lung function are interrelated, with both being associated with shorter survival (Barni et al. 2017). Despite increased life expectancy—61.4 years in the US, 54.0 in Australia, and 51.7 in Europe (CFF 2022b, Ruseckaite et al. 2022, McKone et al. 2021)—lung disease remains a leading cause of morbidity and mortality due to its progression and recurrent exacerbations (Taylor-Robinson et al. 2012). Reductions in FEV1 increase the risk of hospitalizations and death in patients with obstructive lung disease (Taylor-Robinson et al. 2012, Goss et al. 2015).

Since nutritional status can have an impact on the clinical evolution of CF, it is understood that based in a prospective cohort study, it is possible to monitor these patients for a certain period of time, and thus, evaluate their clinical changes. Furthermore, in the state of Santa Catarina there was still no follow-up study for this population. Since nutritional status can have an impact on the clinical evolution of CF, it is understood that based in a prospective cohort study, it is possible to monitor these patients for a certain period of time, and thus, evaluate their clinical changes. Furthermore, in the state of Santa Catarina there was still no follow-up study for this population. Our hypothesis is that the impairment of nutritional status worsens the patient’s clinical condition and leads to early complications of the disease. Therefore, our work aimed to evaluate the influence of the nutritional status on the clinical condition and life expectancy of CF pediatric patients.

MATERIALS AND METHODS

This is a prospective cohort study, carried out in an interdisciplinary outpatient clinic in a reference center for the treatment of CF in the State of Santa Catarina, Brazil, during the period May 2019 - May 2021, comprising the recruitment period (May 2019 - March 2020) and follow-up (until May 2021).

The study included children and adolescents with a confirmed diagnosis of cystic fibrosis by sweat test, aged between 0 and 14 years, 11 months and 29 days - an age range corresponding to the upper limit of care at the hospital where the cystic fibrosis outpatient clinic operates. From the age of 15 onwards, patients are referred to other healthcare institutions specializing in the care of adolescents and adults.

Children and adolescents whose parents and/or guardians refused to answer any of the questionnaires and/or did not allow any of the anthropometric data measurements to be carried out were excluded. Adolescents in the hospital transition phase who had just turned 15 years old were also excluded from the sample. Those who missed scheduled appointments during the data collection period were considered losses. In the second stage of collection, this included participants who had been transferred to the adult CF reference center and those who did not attend the appointment during data collection.

All parents or guardians signed the informed consent form before the study, and children aged 6 years and over and adolescents signed the consent form agreeing to participate in the study. This study was approved by the Research Ethics Committee of the University proposing the study, under CAAE number 00189418.6.0000.5369, and by the Hospital responsible for the outpatient clinic, under CAAE 00189418.6.3001.5361.

Sociodemographic and birth variables

The following data were evaluated: age, gender (female/male), ethnicity (white/black), municipality of origin, paternal and maternal education (< 8 years/> 8 years), family income (1 minimum wage/≥ 2 salaries), maternal smoking during pregnancy and after birth (yes/no), passive smoking (yes/no), birth weight (g), birth length (cm), gestational age (weeks). These data were obtained through interviews with the guardian and from the child’s health record.

Clinical variables

The following data were evaluated: age at diagnosis and at onset of symptoms (in months), relative also with CF (yes - brother/cousin - and no), type of CFTR mutation (F508del or other mutations), hospitalization and pulmonary exacerbation in the last year (yes/no and frequency: none or ≥ 1 time). Meconium ileus (yes/no), pancreatic insufficiency (yes/no), CF-related diabetes (CFRD) (yes/no), gastroesophageal reflux disease (GERD) (yes/no), digital clubbing (yes/no), gastrostomy (yes/no) and pulmonary bacterial colonization (yes/no and frequency: none or ≥ 1 time). All data were collected from medical records.

Nutritional assessment

The anthropometric measurements taken were weight (kg), height (cm), tricipital skinfold thickness (TST, mm) and arm muscle circumference (AMC, cm), which were collected in the outpatient weighing room by a previously trained nutritionist, who followed the recommendations of the BVSMS (2011) and the SBP (2009) for collecting anthropometric data according to age group. Patients were classified by body mass index (BMI) for age into: <50th percentile and ≥50th percentile, according to the Cystic Fibrosis Foundation Pediatric Nutrition Consensus Report (Turck et al. 2016). TST and AMC were assessed according to the work of Frisancho et al. (1999) with values less than or equal to the 5th percentile being considered low. The diagnosis of adipose reserve deficit was made by the TSF value below the 5th percentile and muscle deficit by muscle depletion (AMC below 90% adequacy according to the 50th percentile) (Frisancho et al. 1999). To evaluate nutritional indicators, the WHO Anthro and WHO AnthroPlus programs (Geneva, Switzerland, 2006 and 2007) were used. To evaluate the loss of BMI after one year, the BM for age (BMI/A) percentile values in points (T2 - T1) were used; it was considered that patients with negative values had experienced a decline in nutritional status.

Food intake

Food intake was assessed using a 24-hour dietary recall (24hDR) carried out with the patient and/or guardian during data collection. Diet calculation was evaluated by the AvanutriOnline® program (Avanutri & Nutrição Serviços, Três Rios, RJ, Brazil), and was compared with the Recommended Dietary Allowance (RDA). To calculate food intake, the use of hypercaloric food supplement (unit x day), carbohydrate module (grams x day) and medium chain triglyceride (MCT, ml x day) was considered).

Clinical score

The clinical score used was the Shwachman & Kulczycki (1958) (S-K) score, assessed by the CF team doctor on an outpatient basis. To assess whether there was an improvement or worsening of the clinical condition after one year of follow-up at the service, the total score of the S-K score in points (T2 - T1) was used and those who experienced a score reduction with a worsening of the clinical condition were considered.

Lung function test

The patients’ lung function was assessed by the FEV1 rate, forced vital capacity (FVC), Tiffeneau index (FEV1/FVC) and forced expiratory volume (FEV25-75), with spirometry performed during routine outpatient follow-up in all patients from the age of six years; the data were obtained from the medical records, whose information was filled in by the health professionals according to a protocol established by the service in advance.

Death

The number of deaths was verified in relation to the total number of participants monitored in the study, producing the lethality measure, calculated by the formula: number of deaths/number of cases monitored x 100, expressed in %.

Statistical analysis

The data obtained were compiled and were statistically analyzed using IBM SPSS Statistics software version 21.0. The Kolmogorov-Smirnov normality test was performed to evaluate the hypothesis of distribution of continuous variables normality. Continuous variables with normal distribution were expressed as mean ± standard deviation (SD), while those with asymmetric distribution were expressed as median and interquartile range (IQR). Categorical variables were presented as absolute and relative frequencies. The Chi-Square or Likelihood Ratio test were used to evaluate differences between categorical variables, and t test or U Mann-Whitney for continuous variables. To evaluate the differences in variables between time 1 (T1) and time 2 (T2), the paired Student’s t-test or One-Sample Test for Binomial Proportion were used. A multivariate analysis was performed using Cox regression model to observe the independence of the associations in relation to the outcomes: worsening of the clinical condition, pulmonary exacerbation and nutritional deficit (loss of percentile), considering the variables with a value of p<0.05 and the treatment time at the end of follow-up (T2) as a time variable. The results were expressed as Relative Risk (RR) with 95% CI and considered statistically significant when the p value < 0.05.

RESULTS

At the beginning of the recruitment, out of the total of 117 children and adolescents monitored at the outpatient clinic, 102 agreed to participate in the study. During one year, four patients did not attend their routine appointment, eight were transferred to the adult care center, two died and the sample finally was reduced to 88 patients on follow-up (Figure 1).

Figure 1
Flowchart of the selection of the study population, consisting of children and adolescents with cystic fibrosis.

The main characteristics of the 102 participants were: male (54.9%), white ethnicity (87.3%); most of them were from the region of Greater Florianópolis (27.5%) and 23.5% from the west of Santa Catarina, and had an average age of 6.11±4.63 years. Regarding BMI for age (BMI/A), 11.8% of patients were below the 5th percentile, 20.5% were below the 25th percentile, and 23.5% were below the 50th percentile. During the follow-up period, two deaths occurred, resulting in a fatality rate of 1.96%. The patients who died had BMI/A percentiles of 1.7 and 13.7, respectively, and the cause of death in both cases was respiratory failure.

Regarding parents’ education, the majority had > 8 years of study (74.2% fathers and 88.9% mothers), Family income was ≥ 2 minimum wages (80.2%). Regarding the characteristics at birth, the average weight was 3097.88±463.22 grams, length 48.33±2.50 cm and gestational age 38.70±1.64 weeks. Smoking during pregnancy was reported by 6.9% of mothers and 7.8% reported smoking after birth. The children had a median age at diagnosis of one (1) month, IQR 3, and the onset of symptoms at less than 1 month (0), IQR 1 month. Most did not have a relative with CF (84.2%), 16.7% had meconium ileus and 80.4% presented the CFTR F508del mutation, of which 44.1% are homozygous, 36.3% are heterozygous and 19.6% have other mutations (Table I).

Table I
Sociodemographic and birth characteristics according to body mass index by age in children and adolescents with cystic fibrosis treated at a specialized outpatient clinic, Santa Catarina, 2019-2021.

Variables	Total (n=102)	≥50th (n=45)	<50th (n=57)	p-value	RR (95% CI)
Gender
Male	56 (54.9%)	27 (48.2%)	29 (51.8%)	0.358	1.2 (0.78–1.93)
Female	46 (45.1%)	18 (39.1%)	28 (60.9%)
Ethnicity
White	89 (87.3%)	43 (48.3%)	46 (51.7%)	0.026	3.1 (0.86–11.4)
Black	13 (12.7%)	2 (15.4%)	11 (84.6%)
Relative with CF
Yes	15 (15.8%)	6 (40%)	9 (60%)	0.655	0.8 (0.45–1.68)
No	80 (84.2%)	37 (46.3%)	43 (53.8%)
CFTR mutation
F508del	82 (80.4%)	36 (43.9%)	46 (56.1%)	0.929	0.9 (0.57–1.68)
Other	20 (19.6%)	9 (45%)	11 (55%)
Smoking during pregnancy
Yes	7 (6.9%)	2 (28.6%)	5 (71.4%)	0.457	0.63 (0.19–2.06)
No	94 (93.1%)	43 (45.7%)	51 (54.3%)
Smoking after pregnancy
Yes	8 (7.9%)	3 (37.5%)	5 (62.5%)	0.729	0.8 (0.33–2.08)
No	93 (91.2%)	42 (45.2%)	51 (54.8%)
Family income
1 salary	20 (19.8%)	8 (40%)	12 (60%)	0.647	0.8 (0.48–1.57)
>2 salaries	81 (80.2%)	37 (45.7%)	44 (54.3%)
Paternal education
>8 yrs	72 (74.2%)	33 (45.8%)	39 (54.2%)	0.613	1.1 (0.66–1.97)
< 8 yrs	25 (24.8%)	10 (40%)	15 (60%)
Maternal education
>8 yrs	88 (88.9%)	40 (45.5%)	48 (54.5%)	0.567	1.2 (0.55–2.82)
<8 yrs	11 (11.1%)	4 (36.4%)	7 (63.6%)
Birth weight
>2500g	88 (90.7%)	37 (42%)	51 (58%)	0.074	1.8 (1.2–2.83)
<2500g	9 (9.3%)	7 (77.8%)	2 (22.2%)
	Median (IQR)	Median (IQR)	Median (IQR)
Age (years)	5 (8)	4 (8)	7 (9)	0.341	-
Age at diagnosis (months)	1 (3)	1 (3)	1 (3)	0.501	-
Age at onset of symptoms (months)	0 (1)	1 (2.75)	0 (1)	0.004	-
Birth weight (g)	3050 (640)	2994 (566)	3100 (555)	0.297	-
Length at birth (cm)	48 (2.88)	47.5 (2.5)	48 (3)	0.045	-
Gestational age (weeks)	39 (2.0)	39 (1.5)	39 (2)	0.084	-

• Legend: CF = cystic fibrosis; CFTR = cystic fibrosis transmembrane conductance regulator; IQR: interquartile range. *expressed in months. **expressed in weeks. ▫comparison between percentiles using the Chi-square test; # comparison between percentiles using Fisher’s Exact test ∞comparison between percentiles using test U Mann-Whitney.

Regarding the nutritional status of patients throughout the year of study monitoring, it was observed that two (2) patients showed improvement in nutritional status, while nine (9) showed worsening. The median BMI/A percentile of patients classified below the 50th percentile was 73.4, with an IQR of 25.22. Among patients with BMI/A above the 50th percentile, the median was 19.2, with an IQR of 27.2.

When comparing the BMI/A percentiles, it was observed that the majority of black ethnicity patients were in the <50th percentile of BMI/A (84.6%) and those who were in the >50th percentile of BMI/A had a later onset of symptoms compared to those in the <50th percentile of BMI/A. Patients in the ≥ 50th percentile of BMI/A had shorter length at birth compared to those in the < 50th percentile of BMI/A (Table I).

When comparing BMI/A percentiles at baseline, it was observed that patients in the BMI/A percentile < 50 experienced more GERD (87.5% vs. 12.5%, p=0.045) (Table II). When comparing the other variables, no significant differences were observed between the BMI/A percentiles. Regarding the nutritional status of patients in relation to pancreatic function, the median BMI/A of individuals with pancreatic insufficiency was 15.9, with an IQR of 2.9, while among those with pancreatic sufficiency the median value was 15.7, with an IQR of 2.1. At baseline, 5.9% of individuals had CFRD, with a mean age of 13.5±0.55 years and after one year, 2.3% of individuals had CFRD, with a mean age of 10.5±2.12, when comparing the percentiles there was no difference between the groups. There was no statistically significant difference between the groups (Table II and III).

Table II
Clinical characteristics according to body mass index by age in children and adolescents with cystic fibrosis treated in a specialized outpatient clinic, Santa Catarina, 2019-2021.

Evaluated data	Baseline (n= 102)		p-value	RR (95% CI)	After 1 year (n = 88)		p-value	RR (95% CI)
	Percentile ≥50 (n = 45)	Percentile < 50 (n = 57)			Percentile ≥ 50 (n = 59)	Percentile < 50 (n = 29)
Passive smoking Yes No	4 (33.4%) 41 (45.6%)	8 (66.7%) 49 (54.5%)	0.423▫	0.73 (0.31-1.68)	6 (66.7%) 53 (67.1%)	3 (33.3%) 26 (32.9%)	0.980▫	1.0 (0.61-1.63)
S-K score Excellent. good and light Moderate and severe	45 (45.9%) -	53 (54.1%) 4 (100%)	0.070	0.54 (0.45 – 0.65)	58 (66.7%) 1 (100%)	29 (33.3%) -	0.481	0.67 (0.57-0.77)
No. of Hospitalizations* None ≥ 1 time	36 (46.2%) 6 (37.5%)	42 (53.8%) 10 (62.5%)	0.526	1.2 (0.62-2.42)	57 (67.1%) 2 (66.7%)	28 (32.9%) 1 (33.3%)	0.989▪	0.9 (0.19-5.03)
Exacerbation* None ≥ 1 time	35 (50.7%) 7 (28%)	34 (49.3%) 18 (72%)	0.050▫	1.18 (0.93 – 3.54)	31 (73.8%) 28 (60.9%)	11 (26.2%) 18 (39.1%)	0.197▫	1.21 (0.90-1.62)
Bacterial Colonization no.* None ≥ 1 time	6 (37.5%) 36 (46.2%)	10 (62.5%) 42 (53.8)	0.526	0.81 (0.41-1.60)	2 (66.7%) 57 (67.1%)	1 (33.3%) 28 (32.9%)	0.989	0.94 (0.44–2.24)
GERD Yes No	1 (12.5%) 44 (46.8%)	7 (87.5%) 50 (53.2%)	0.045▪	0.27 (0.42-1.69)	4 (66.7%) 54 (67.1%)	2 (33.3%) 27 (32.9%)	0.984▪	0.99 (0.53-1.78)

• Legend: S-K score: Shwachman-Kulczycki score; GERD: gastroesophageal reflux disease; RR: relative risk; *Referring to the year prior to the one analyzed; #comparison between percentiles using Student’s t test; ▫comparison between percentiles using the Chi-square test; ▪comparison between percentiles using the likelihood ratio test.

Table III Clinical and lung function characteristics according to body mass index by age in children and adolescents with cystic fibrosis treated in a specialized outpatient clinic, Santa Catarina, 2019-2021.

Evaluated data	Baseline (n= 102)		p-value	After 1 year (n = 88)		p-value
	Percentile ≥ 50 (n = 45)	Percentile < 50 (n = 57)		Percentile ≥ 50 (n = 59)	Percentile < 50 (n = 29)
Hospitalization* Yes No	10 (40%) 32 (46.4%)	15 (60%) 37 (53.6%)	0.583▫	16 (57.1%) 43 (71.7%)	12 (42.9%) 17 (28.3%)	0.177▫
Pancreatic insufficiency Yes No	40 (42.1%) 5 (71.4%)	55 (57.9%) 2 (28.6%)	0.130▪	57 (66.3%) 2 (100%)	29 (33.7%) -	0.203▪
CFRD Yes No	1 (16.7%) 44 (45.8%)	5 (83.3%) 52 (54.2%)	0.141▪	1 (50%) 58 (67.4%)	1 (50%) 28 (32.6%)	0.615▪
Digital clubbing Yes No	8 (32%) 37 (48.1%)	17 (68%) 40 (51.9%)	0.160▫	21 (61.8%) 38 (70.4%)	13 (38.2%) 16 (29.6%)	0.403▫
Gastrostomy Yes No	2 (33.3%) 43 (44.8%)	4 (66.7%) 53 (55.2%)	0.579▪	5 (83.3%) 54 (65.9%)	1 (16.7%) 28 (34.1%)	0.353▪
	Mean ± SD	Mean ± SD		Mean ± SD	Mean ± SD
Treatment time**	5.06±4.11	6.18±4.78	0.212◘	6.00±3.87	5.87±4.38	0.905◘
Age (years)	5.50±4.28	6.60±4.87	0.339◘	6.41±4.11	6.24±4.56	0.817◘
FVC %	96.06±26	87.92±26.65	0.348◘	98.17±22.45	97.82±21.18	0.971◘
FEV1 %	82.85±25.66	73.30±26.36	0.281◘	79.83±23.19	75±23.53	0.568◘
FEV1/FVC%	85.57±18.69	97.71±35.45	0.253◘	76.94±8.83	81.88±21.95	0.495◘
FEV25-75 %	62.27±28.70	56.74±26	0.606◘	53.52±25.05	52.78±25.27	0.917◘

Legend: CFRD: cystic fibrosis-related diabetes; FVC: forced vital capacit_y; FEV1: forced expiratory volume in the first second; FEV1/FVC: Tiffeneau inde_x; _FEV25-75: forced expiratory volume; *Referring to the year prior to the year analyzed; **expressed in years, considering age at diagnosis and current age. #comparison between percentiles using Student’s t test; #comparison between percentiles using the Chi-square test; ▪comparison between percentiles using the likelihood ratio test.

When comparing the BMI/A percentiles at baseline, it was observed that patients in the BMI/A percentile < 50 had more muscle tissue depletion (70% vs. 30%, p = 0.012). After one year, those in the BMI/I percentile > 50 had a significantly higher average weight (27.12±14.54 kg vs. 20.90±11.96 kg, p = 0.040). However, it was observed that those who were in the BMI/A percentile > 50 showed an increase in weight from 23.27±14.80 kg to 27.12±14.54 kg and those who were in the BMI/I percentile < 50 reduced their weight from 22.19±13.34 kg to 20.90±11.45 kg, as detailed in Table IV.

Table IV
Anthropometric characteristics and food intake according to body mass index by age in children and adolescents with cystic fibrosis receiving care at a specialized outpatient clinic, Santa Catarina, 2019-2021.

Evaluated data	Baseline (n= 102)		p-value	After 1 year (n = 88)		p-value
	Percentile ≥ 50 (n = 45)	Percentile < 50 (n = 57)		Percentile ≥50 (n = 59)	Percentile < 50 (n = 29)
AMC < p 5th ≥ p 5th	12 (30%) 9 (69.2%)	28 (70%) 4 (30.8%)	0.012▫	18 (62.1%) 16 (76.2%)	11 (37.9%) 5 (23.8%)	0.291▫
TST < p 5th ≥ p 5th	1 (50%) 20 (39.2%)	1 (50%) 31 (60.8%)	0.762▪	- 34 (68%)	- 16 (32%)	-
Hypercaloric food supplement Yes No	24 (38.1%) 21 (53.8%)	39 (61.9%) 18 (46.2%)	0.119▫	36 (61%) 23 (79.3%)	23 (39%) 6 (20.7%)	0.086▫
LIP and/or CHO module Yes No	14 (35%) 31 (50%)	26 (65%) 31 (50%)	0.136▫	25 (61%) 34 (72.3%)	16 (39%) 13 (27.7%)	0.258▫
Vitamin D supplement Yes No	32 (41%) 13 (54.2%)	46 (59%) 11 (45.8%)	0.257▫	56 (67.5%) 3 (60%)	27 (32.5%) 2 (40%)	0.734▪
EER% < 150% > 150%	35 (44.3%) 10 (43.5%)	44 (55.7%) 13 (56.5%)	0.944▫	49 (70%) 10 (55.6%)	21 (30%) 8 (44.4%)	0.245▫
	Mean ± SD	Mean ± SD		Mean ± SD	Mean ± SD
Weight (kg)	23.27±14.80	22.19±13.34	0.625◘	27.12±14.54	20.90±11.45	0.040◘
Height (m)	1.09±0.29	1.14±0.34	0.417◘	1.18±0.26	1.13±0.28	0.432◘
AC (cm)	17.05±4.25	16.50±2.75	0.924◘	17.25±3.75	15.48±3.20	0.074◘
AMC (cm)	15.45±2.84	14.03±1.98	0.070◘	15.48±3.24	14.02±1.93	0.054◘
TST (mm)	14.43±4.51	12.50±3.49	0.118◘	12.65±3.30	11.88±2.94	0.253◘
EER (kcal/day)	1464.39±602.35	1441.49±732.38	0.551◘	1725.08±687.03	1615.37±664.50	0.252◘
Protein (g/day)	59.61±41.09	55.04±31.29	0.960◘	65.76±26.86	62.29±44.68	0.190◘
Carbohydrate (g/day)	182.23±70.75	190.96±103.04	0.800◘	228.24±98.50	212.76±79.77	0.399◘
Lipid (g/day)	53.38±9.07	52.20±30.24	0.644◘	60.51±28.85	58.46±28.28	0.667◘
Vitamin D (μg/day)	8.44±9.07	6.24±5.32	0.349◘	7.11±6.37	7.50±9.83	0.555◘
Vitamin A (μg/day)	470.06±349.74	387.26±273.12	0.262◘	426.81±305.09	413.54±296.10	0.873◘
Vitamin E (mg/day)	12.56±10.95	9.42±6.65	0.119◘	14.58±15.62	11.74±8.34	0.746◘
Sodium (g/day)	1556.70±933.44	1335.56±841.41	0.256◘	1688.73±707.78	1701.81±825.65	0.908◘
Potassium(g/day)	1288.11±701.60	1209.25±694.36	0.533◘	1445.67±646.85	1425.41±629.13	0.729◘

• Legend: AC: arm circumference; AMC: arm muscle circumference; TST: triciptal skinfold thickness; LIP: lipid; CHO: carbohydrate; EER: Estimated Energy Requirement. ▫comparison between percentiles using the Chi-square test; ▪comparison between percentiles using the likelihood ratio test; ◘comparison between percentiles using Student’s t test.

After one year of follow-up, significant changes were observed in several variables evaluated. There was an increase in the number of exacerbations (median 1.0 [0.0–1.0] to 2.0 [1.0–2.0]; p = 0.001) and in bacterial colonization (p = 0.003). Regarding nutritional status, there was an increase in body mass index for age (%) (42.3 [30.0–58.0] to 62.5 [45.0–75.0]; p < 0.001), BMI percentile (15.7 [15.0–16.5] to 16.6 [15.9–17.3]; p < 0.001) and EER value (1626 [1580–1675] to 1660 [1600–1695]; p < 0.001). In the analysis of categorical variables, the proportion of patients with at least one exacerbation increased from 26.3% to 51.2% (p = 0.003), while the presence of exacerbations in the last year decreased from 67.0% to 48.0% (p = 0.004). The occurrence of gastroesophageal reflux reduced from 8.0% to 6.8% (p = 0.017), while the presence of digital clubbing increased from 20.5% to 38.6% (p < 0.001). In the BMI classification, a reduction in eutrophy (82.9% to 73.9%) and an increase in the risk categories of overweight, overweight, and obesity (p = 0.001) were observed (Table V).

Table V
Comparison of clinical variables between baseline (T1) and after 1 year (T2), in children and adolescents with cystic fibrosis treated in a specialized outpatient clinic, Santa Catarina, 2019-2021.

Variable	N	T1	T2	p-value
Continuous variables		Median (IQR)	Median (IQR)
S-K score	88	90 (82-97)	95 (88-102)	0.163▫
FEV1%	88	78,3 (70.0–82.5)	78.5 (70.5–83.5)	0.992▫
FVC%	88	75.0 (72.0-77.0)	77.5 (75.0-80.0)	0.328▫
Number Exacerbation	88	1.0 (0.0-1.0)	2.0 (1.0-2.0)	0.001▫
Bacterial Colonization No.*	88	1.0 (0.0–1.0)	1.0 (1.0–1.0)	0.003
BMI Age%	88	42.3 (30.0–58.0)	62.5 (45.0–75.0)	<0.001▫
BMI Percentile	88	15.7 (15.0-16.5)	16.6 (15.9-17.3)	<0.001▫
EER	88	1626 (1580–1675)	1660 (1600–1695)	<0.001▫
Categorical variables		n (%)	n (%)
Exacerbation (yes/no)	88	59 (67.0%) / 29 (33.0%)	42 (48.0%) / 46 (52.0%)	0.004▪
Exacerbation (none/ ≥ 1 time)	80	59 (73.7%) / 21 (26.3%)	39 (48.8% / 41 (51.2%)	0.003▪
GERD (yes/no)	88	7 (8.0%) / 81 (92%)	6 (6.8%) / 82 (93.2%)	0.017▪
Digital clubbing (yes/no)	88	18 (20.5%) / 70 (79.5%)	34 (38.6%) / 54 (61.4%)	<0.001▪
BMI classification (%) Marked thinness Thinness Eutrophy At risk of overweight Overweight Obesity	88	2 (2.3%) 2 (2.3%) 73 (82.9%) 4 (4.5%) 6 (6.9%) 1 (1.1%)	1 (1.1%) 1 (1.1%) 65 (73.9%) 7 (8%) 10 (11.4%) 4 (4.5%)	0.001▪

• Legend: S-K score: Shwachman-Kulczycki scor_e; FEV1: forced expiratory volume in the first second; FVC: forced vital capacity; BMI: body mass index; GERD: gastroesophageal reflux disease; EER: Estimated Energy Requirement. *Referring to the year prior to the one analyzed; ▫comparison between using the Wilcoxon test; ▪comparison between using the test McNemar test. IQR: interquartile range.

DISCUSSION

The present study demonstrated that the predominant population was male and of white ethnicity, corroborating with the last Brazilian record of CF (GBFC 2021) and the American record of CF (CFF 2022b), which showed that 51.22% and 51.7% of those diagnosed with CF are male, while 69.04% and 91.2% are of white ethnicity. Ethnicity characteristics may also be related to the location studied, in the southern region of Brazil, with predominantly European colonization (IBGE 2023). The F508del mutation was the one with the highest prevalence in the study, which agrees with the literature, since around 50% of individuals with the disease are homozygous and have one copy of the F508del mutation (Lusman & Sullivan 2016). In our study, most black patients were in the <50th percentile. Our explanation for this is that these patients had lower socioeconomic status, lower paternal and maternal education, and lower adherence to treatment, as well as in routine outpatient consultations. Children and adolescents who presented with a later onset of symptoms had a BMI/A > 50th. CF presents a wide spectrum of disease manifestations, which can range from single to multisystem involvement and from mild to severe disease (Hart el at. 2004). These patients probably have a mild disease, which leads to a lower impact of the disease on growth and nutritional status (Kerem et al. 2014). In our study patients with BMI/A < 50th percentile had more GERD, which can contribute to nutritional deficit, as it can lead to esophagitis, structuring disease and hypoproteinemia (Lusman & Sullivan 2016). In a study carried out in Bahrain, the authors found that GERD was one of the significant risk factors for malnutrition in patients with CF (Woestenenk et al. 2014b).

Children who had received a CF late diagnosis were at greater risk of having nutritional deficits and pulmonary exacerbations. Early diagnosis facilitates intervention in nutritional status, which is mainly affected by pancreatic insufficiency and malabsorption. Furthermore, it allows the monitoring of the growth curve and the detection of pathogen colonization in the upper airways, which are strongly related to a worse prognosis (Papalexopoulou et al. 2018). Therefore, monitoring growth and nutritional status is crucial for early intervention, effective treatment and rehabilitation of CF patients.

BMI is the most widely accepted measure to assess the nutritional status of CF patients. According to the European Society for Clinical Nutrition and Metabolism (ESPEN) guidelines, these patients must reach > 50th percentile of BMI for a better prognosis of the condition (Turck et al. 2016). Despite constant monitoring and nutritional guidelines, a BMI ≥ 50th percentile can be difficult to achieve, as seen in the present study, in which 55.9% of patients did not reach this recommendation. The literature demonstrates that nutritional status has a significant impact on the prognosis of lung disease in patients with CF, since malnutrition is a consequence of increased energy consumption, low food intake and poor absorption of nutrients (Lusman & Sullivan 2016). As the loss of muscle mass reduces the resistance of the respiratory muscles, this impairs the function of the diaphragm, in addition to impairing the immune function, which favors recurrent infections, in addition to increasing energy demand, worsening the pulmonary condition (Hart et al. 2004). Studies demonstrate the negative effect of malnutrition on the respiratory function and prognosis (Kerem et al. 2014, Woestenenk et al. 2014b), although, in the present study, lung function is not related to nutritional status. However, patients with a BMI <50th percentile had the lowest spirometry averages.

When analyzing the anthropometric characteristics of the patients in the present study, no significant differences were observed between the percentiles. However, after one year of follow-up, patients who were in the <50th BMI percentile had the lowest average weight. CF causes the development of several phenotypes, some of which are more severe, which results in difficulties in weight gain, linear growth and maintenance of nutritional status in childhood. Furthermore, those in the <50th percentile tend to have greater difficulty gaining weight (Lusman & Sullivan 2016). It is important to emphasize that, unlike adults, children and adolescents are in a growth phase. The speed of growth in the postnatal period is particularly high until the first two years of life, with a gradual and pronounced decline until the age of five. From the fifth year onwards, growth speed is practically constant, 5 to 6 cm/year until the beginning of the adolescence growth spurt (SBP 2009).

However, other measurements are important to assess nutritional status, such as TST and AMC. BMI is not the only indicator of nutritional status, since the body is made up of two main components: fat mass and fat-free mass (Calella et al. 2018). Fat-free mass correlates more strongly than BMI regarding the respiratory muscle function, and the depletion of muscle tissue is directly related to the patient’s poor prognosis, due to a more severe lung condition (Turck et al. 2016, Papalexopoulou et al. 2018). In the present study, the majority of patients were depleted of muscle tissue by AMC. However, in the study by Phong et al. (2020) only 49% of patients had a deficit in muscle mass assessed by AMC. CF patients present a chronic state of metabolic stress linked to pulmonary exacerbations, which affects energy balance and protein metabolism, consequently compromising fat reserves and mainly protein body mass (Althanazio et al. 2017). Therefore, AMC can serve as an early indicator of nutritional status deterioration, since regardless of BMI/A percentile, patients presented depletion of muscle tissue.

The literature shows that around 30% of children and adolescents with CF have low BMI and fat-free mass, which results in a decrease in lung function, an increased frequency of pulmonary exacerbations and, consequently, hospitalizations (Engelen et al. 2014). However, in this study, nutritional status was not associated with the lung function, pulmonary exacerbations and the number of hospitalizations. This may be due to the fact that these patients were monitored by a multidisciplinary team in a reference hospital.

Nutrient intake recommendations aim to meet individuals’ nutritional needs. To do this, the estimated energy need must be calculated, that is, the consumption necessary to meet the energy balance compatible with a good state of health. As the child grows, this value changes, as it is based on age, height, weight and activity factor (Trumbo et al. 2002). As predicted in the literature, after one year follow-up, patients showed an increase in the value of daily intake and consumption of macronutrients, sodium and potassium. Regarding food intake, the majority of patients did not reach 150% of the RDA recommendations for energy, both at the beginning and at the end of the study. These findings are in line with the findings by Chaves et al. (2015), who observed that only 19.6% of the sample members ingested the minimum recommended RDA for CF patients, values similar to those observed in two other studies (Woestenenk et al. 2014a, Martins et al. 2020).

Passive smoking affects the respiratory health of CF patients, decreasing FEV₁; furthermore, the reduction of food intake can cause micronutrient deficiency, wich retards the growth of children, even those children not affected by CF (Kopp et al. 2016). Passive smoking has been associated with decreased linear growth in children with CF between 6 and 11 years of age, as well as the decrease in linear growth and weight throughout the first year of life of CF babies (Kopp et al. 2016). In the present study, most children with a BMI below the 50th percentile had mothers who smoked during and after pregnancy, resulting in passive smoke exposure. However, this was not identified as an associated factor. According to a study by Kopp et al (2019), children with CF exposed to smoke showed a decrease in prostaglandin D₂ concentrations and weight z-score, in addition to having more hospitalization episodes. In the study by Oates et al (2021), which evaluated 3663 individuals with CF, cessation of smoke exposure was associated with an improvement in FEV₁, an increase in the BMI percentile and a reduction in the chances of developing a pulmonary exacerbation.

CFRD is a relevant clinical condition that has significant clinical implications in CF, as it is associated with a greater risk of malnutrition and, increased lung infections and early mortality (Prentice et al. 2021). CFRD mainly affects children and older adults, but recent studies have shown that it can manifest itself from the beginning of life (Yi et al. 2016, Prentice et al. 2019). In their study, Ararat et al. (2021) found that patients with CFRD showed reduced growth velocity, reduced weight gain and lower BMI compared to patients without CFRD. In our study, the majority of patients with CFRD were in the <50th percentile, which corroborates the observations reported in the literature.

After one year of follow-up, a significant increase in the number of exacerbations and bacterial colonization was observed, despite improvements in nutritional indicators. This finding suggests that, even with increases in BMI-for-age, BMI percentile, and EER, the nutritional benefits did not translate into a reduction in respiratory morbidity. In patients with cystic fibrosis, nutritional status is closely associated with lung function and survival, being one of the main predictors of prognosis (Stephenson et al. 2013, Stallings et al. 2008). Studies show that intensive nutritional support can improve weight gain and maintain lung function, but the presence of chronic infection with Pseudomonas aeruginosa and other opportunistic bacteria remains an important factor in clinical decline (Turck et al. 2016, Courtney et al. 2007).

The increased prevalence of digital clubbing observed in this study may reflect the progression of chronic lung disease, even with stable FEV₁ and FVC. This reinforces the idea that isolated spirometric parameters may not capture structural or subclinical changes, requiring integrated clinical assessment and the use of complementary tests, such as high-resolution CT, to better characterize disease progression (Loeve et al. 2009).

The reduction in the proportion of eutrophic patients and the increase in the categories of overweight, overweight, and obesity also warrant attention. Although improved BMI is associated with better outcomes in CF, excess weight can introduce new challenges, including insulin resistance and a increased risk of cystic fibrosis-related diabetes (Hanna & Weiner 2015, Szentpetery et al. 2022). Therefore, nutritional monitoring strategies should aim not only to prevent malnutrition but also to avoid excess weight, maintaining an optimal balance between nutritional status and metabolic health.

We believe it is important to highlight the excellent work of the multidisciplinary team at the cystic fibrosis center in their continuous efforts to promote adequate nutrition for all patients. Nutritional care remains a cornerstone in the treatment of cystic fibrosis, playing a key role in improving quality of life and managing disease-related complications. The team, comprised of nutritionists, physicians, and other health professionals, has shown a strong commitment to individualized care, providing tailored support to optimize each patient´s nutritional status. The various nutritional strategies implemented, including customized diets and the use of dietary supplements, demonstrate the effectiveness of collaborative and integrated approach. The outcomes observed in this study, which reflect the positive impact of nutritional interventions, reinforce the importance of specialized nutritional monitoring in cystic fibrosis referral centers, with a focus on continuous improvement and better patients’ outcomes.

Regarding the limitations of the study, the possibility of information bias should be taken into account, due to the collection of part of the data in the medical records and the analysis of food consumption being based on only one dietary record, which can mask errors when excluding unusual days. It is important to highlight that the data are recorded based on a protocol previously established by the service, in order to ensure quality recording. Although the small sample size has limited some comparative assessments, such as death risk factors, it is emphasized that the study took place in a reference center for the treatment of CF children and adolescents from birth to 14 years of age, with the aim of capturing all the data of the patients that were monitored at the service. However, the concomitance of the COVID-19 pandemic during the patient follow-up period may have contributed to some losses to follow-up.

CONCLUSIONS

It is concluded that compromised nutritional status was a risk factor for earlier onset of symptoms, GERD, muscle tissue depletion, and low body weight. Despite interdisciplinary follow-up and adherence to strict protocols, further studies similar to ours are needed to support changes in clinical protocols and guidelines aimed at improving the clinical condition and nutritional status, thereby ensuring a better quality of life for these patients.

Acknowledgements

The authors are grateful to the Santa Catarina State Research and Innovation Support Foundation for granting a doctoral scholarship to Dr. Bruna Becker da Silva, and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for Research Productivity scholarship for BPMI. This study was funded by FAPESC Public Call No. 03/2017, Process No. 23038.013359/2017-71 and conducted within the scope of the Postgraduate Program in Health Sciences at the University of Southern Santa Catarina, Tubarão/SC, Brazil. The funding body had no role in designing the study and collecting, reviewing and interpreting the data and in writing the manuscript.

• Data availability
  The data are not publicly available due to ethical restrictions and patient confidentiality.

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Data availability

The data are not publicly available due to ethical restrictions and patient confidentiality.

Publication Dates

• Publication in this collection
  16 Feb 2026
• Date of issue
  2026

History

• Received
  18 May 2024
• Accepted
  22 Aug 2025