Cystic fibrosis (CF) is the most common inherited disease in the white population and is caused by mutations in the CF transmembrane conductance regulator gene. Most patients with CF have pancreatic insufficiency (PI) and are at risk for maldigestion, malabsorption, and low energy intake in relation to increased fecal nutrient loss. The negative impact of underweight on the long-term outcome of patients with CF has long been recognized (1). In the past malnutrition was common and considered an intrinsic clinical feature of the disease; however, the iatrogenic nature of nutritional failure in CF subsequently has been established, and malnutrition and growth retardation are no longer acceptable in any patient with CF (2).
Data from patient with CF registries in North America, Europe, and Australia have documented an improvement in nutritional status during the last 2 decades, with parallel improvements in lung function and survival (3-6). Despite these major achievements, nutritional failure remains a problem for many patients with CF. Lai et al (7) identified infants and adolescents as the 2 age groups with the highest rate of malnutrition that should, therefore, represent the main target for strict nutritional surveillance.
A timely nutritional intervention is of major importance because infants with CF often show subnormal growth throughout the first year of life if treatment is delayed (8). Patients with early malnutrition are at risk for having worse lung function even in cases in which some degree of catch-up growth has occurred (9); in addition, short stature (height for age <5th percentile) has been recognized as a significant prognostic indicator of survival (10).
For all of these reasons, nutritional management has become an important aspect of the multidisciplinary approach to CF (11). Simple anthropometric indicators have been used to classify malnutrition in patients with CF, including height-for-age, weight-for-age, weight-for-height (ie, percent ideal body weight, IBW%), and body mass index (BMI) percentiles (12,13). The degree of nutritional failure varies among studies due to different criteria used to classify malnutrition.
In 2002, the Cystic Fibrosis Foundation (CFF) Consensus Report recommended the combined use of the following parameters to evaluate nutritional status: height-for-age percentile (HAP), percent ideal body weight (IBW%), BMI percentile (BMIp) between 2 and 20 years, and weight-for-length percentile (WLP) for children younger than 2 years of age (12). The recommended values to identify malnutrition were HAP <5th, IBW% <90th and BMIp <10th. More recently, BMIp has been shown to be more reliable than IBW% in both North American and European CF populations (14,15). BMIp can be easily determined and is less prone to misclassification than IBW%; BMIp <15th has been indicated as the optimal cutoff for defining malnutrition in patients with CF, and the CFF has recommended the new nutritional goal of BMIp ≥50th (16).
In view of the increasing evidence of the impact of nutritional status on the clinical course of CF, we carried out a multicentre, cross-sectional study to evaluate anthropometrics and growth in Italian patients with CF. The collection of data in a formal multicentre study has for the first time allowed the characterization of nutritional status using 3 different auxologic indicators and the identification of the most critical age intervals and risk factors for malnutrition in a large cohort of Italian patients with CF. In addition, data have been analysed to assess differences among centres in nutritional outcomes as a basis for a quality improvement project.
PATIENTS AND METHODS
We carried out a cross-sectional, multicentre study involving 10 Italian Reference CF centres that enrolled all patients younger than 18 years on regular follow-up during the period January 2005 to December 2006. All patients had been diagnosed according to international standards (17); neonatal screening was the most common modality of diagnosis, as only 3 of the 10 participating centres did not have a neonatal screening program for CF. A total of 892 patients with CF (452 males, 50.7%), mean age 9.2 ± 6.4 years (ranging from 1 month to 18 years) were recruited.
The number of patients in each of the 10 centres ranged from 17 to 309. Height and weight were measured (when the patient was in a stable clinical condition) by specifically trained personnel and the values entered in a database that also contained demographic and clinical data of the patients. BMI was also calculated on the basis of weight in kilograms/(height in meters)2 ratio.
Reproducibility in anthropometric measurement was evaluated by comparing measures obtained with standard instruments in all centres with those obtained with reference instruments in a sample of patients.
The presence of nutritional failure was defined using 3 different anthropometrical parameters recommended in the literature (HAP, WLP, BMIp) (12,15): HAP <5th was calculated in all patients, WLP <10th in patients <2 years, and the BMIp <15th in patients between 2 and 18 years.
The presence of malnutrition was analysed in relation to age. For this purpose, patients were divided into the following age groups: 0 to 2, 2 to 5, 5 to 10, 10 to 14 and 14 to 18 years. We also evaluated the trend with age of the 3 parameters, comparing patients with nutritional failure (HAP <5th, WLP <10th and BMIp <15th) alone and together with those at risk for malnutrition (HAP <25th, WLP <25th and BMIp <25th). Intercentre differences in HAP, WLP, and BMIp were also evaluated, including differences in the percentage of patients not fulfilling the new BMI goal (BMIp ≥ 50th).
The presence of PI was defined by means of faecal elastase-1 measured by immune-enzymatic method (18), with a cutoff value of 200 μg/g of faeces or a 72-hour stool fat loss >7 g/day. A history of meconium ileus (MI) was also investigated. FEV1 was calculated in patients aged 6 to 18 years (n = 620), able to perform spirometry.
z Scores for height, weight and BMI were used to determine the relation of nutritional status with sex, PI, MI, and lung function.
SAMPLE SIZE AND STATISTICAL ANALYSIS
A sample size of 1000 patients was considered sufficient with a power of 99% to detect a difference between patients and the normal population of 0.15 z score units at the 0.05 significance level.
Data were controlled for quality, with evaluation of consistency and missing values during data collection. The proportions of malnourished patients alone (HAP<5th) and together with those at risk of malnutrition (HAP<25th) were compared by calculating odds ratio (OR) and 95% confidence interval (CI). χ2 test was used for testing statistical significance.
HAP, WLP, BMIp, and weight and height z scores were calculated using the NutStat Software included in the Epi-Info software (Centers for Disease Control and Prevention [CDC], Atlanta), taking as reference CDC 2000 normal figures (19). Data analysis was performed with the SPSS (Chicago, IL) and Stata (College Station, TX) software packages. Box plots were used to describe auxologic parameters together with mean values and standard deviations. Student t test was used to compare means after controlling for homoscedasticity, whereas the χ2 test was used to compare proportions. Pearson correlation coefficients were calculated to evaluate correlation between FEV1 and auxologic measures.
RESULTS
Clinical and demographic characteristics of the study population are summarized in Table 1.
Nutritional Status of the Whole CF Population
Nutritional assessment on the basis of the 3 auxologic parameters in the whole patient population is reported in Table 2. Mean values were 40.2 ± 29.4 for HAP, 45.5 ± 29.9 for WLP, and 47.9 ± 30.9 for BMIp. Values >25th percentile were found in 59.8% of the whole population for HAP, in 64.4% of patients younger than 2 years for WLP, and in 69.5% of those aged 2 to 18 years for BMIp. In this latter group, 54.4% of patients had a BMIp<50th and thus did not fulfill the new BMI goal. Nutritional failure was observed in 25.6% of patients considering any criteria, ranging from 12.2% using only HAP to 20.9% with BMIp.
We then compared the distribution of patients in the 3 different categories of nutritional status (adequate, at risk, nutritional failure) using HAP, WLP, and BMIp (Table 3). Although HAP and WLP gave a similar distribution of patients younger than 2 years of age within the different categories of nutritional status, after the age of 2 years, BMIp and HAP gave substantially different results. Compared with HAP, BMIp classified a higher number of patients with nutritional failure (164 vs 93) and with adequate nutrition (548 vs 464), whereas HAP classified a 3-fold higher number of patients at risk for malnutrition compared to BMIp (231 vs 76). Using HAP, 324 patients (41.1% of our population >2 years) were classified as malnourished or at risk of malnutrition, compared with only 240 using BMIp (30.5%).
We compared the performance of BMIp<15th vs HAP<5th and observed an agreement of 76.6% with a positive predictive value (PPV) of 37.7%. Agreement further decreased when we compared BMIp<25th and HAP<25th (58.1%) with a PPV of 35.6%.
Growth Assessment in Relation to Age
Figure 1 shows the occurrence of nutritional failure in patients with CF divided into 5 age groups. Whatever the parameter used for calculation, the highest rate of nutritional failure was documented starting in adolescence through early adulthood (11-18 years). HAP<5th and BMIp<15th identified malnourished patients in 11.7% and 20.1% of patients aged 10 to 14 years, respectively, and in 21.9% and 27.9% of those aged 14 to 18 years.
The proportion of patients with inadequate nutritional status was significantly higher in the group aged 14 to 18 years, with both HAP<5th (OR 2.4, 95% CI 1.5-3.9; P < 0.001) and HAP<25th (OR 2.2, 95% CI 1.5-3.1; P < 0.001).
In the group of patients aged 0 to 2 years, nutritional failure was observed in 15.4% and 12.9% of patients using HAP<5th and WLP<10th, respectively. When comparing this group with older children, the proportion of malnourished patients was not statistically different with both HAP<5th (OR 1.4, 95% CI 0.75-2.6; P = 0.25) and HAP<25th (OR 0.7, 95% CI 0.5-1.2; P = 0.15).
We then compared the trend with age of the 3 parameters. Curves were drawn by inserting values by single year. Figure 2 refers to the proportion of patients with nutritional failure (HAP<5th, WLP<10th, and BMIp<15th), whereas Figure 3 refers to the proportion of patients at risk for malnutrition (HAP<25th, WLP<25th, and BMIp<25th). In both figures HAP and WLP have a similar profile during the first year of life. In contrast, during the second year, WLP increases, whereas HAP decreases. HAP and BMIp have the same trend, with a decline in the prepubertal age group and a clear increase during adolescence. However, BMIp<15th seems to be a better indicator of malnutrition than HAP<5th, especially in the prepubertal age group and in patients older than 15 years. The trend of HAP and BMIp completely inverts when we consider patients <25th percentile. In fact, the frequency of BMIp<25th was consistently lower than HAP<25th in patients aged 3 to 17 years, especially during adolescence.
Relation of Nutritional Status With Sex, PI, MI, and Lung Function
z Scores for height, weight, and BMI were calculated in all patients and analysed according to sex, PI, MI, and FEV1. No differences in nutritional status were detected with regard to sex and MI (mean z scores for height and weight, and BMI in males: -0.52, -0.28, -0.32; females: -0.32, 0.13, -0.14; P = 0.50; 0.17, 0.44, respectively; MI: -0.44, -0.68, -0.42; No MI: -0.42, 0.03, -0.2; P = 0.95; 0.10, 0.53, respectively). Patients with PI showed lower mean z scores for height, weight, and BMI (-0.60, -0.22, -0.37) as compared with patients with pancreatic sufficiency (0.14, 0.39, 0.23, respectively) with a statistically significant difference for height and BMI z scores (P = 0.03 and 0.03, respectively). All z scores showed a direct correlation with FEV1, as shown in Figure 4 (correlation coefficients for height, weight, and BMI: 0.095, 0.092, 0.298; P = 0.03, 0.04, <0.01, respectively).
Comparison of Nutritional Status Among Centres
Differences between centres were evaluated by comparing the rate of nutritional failure as defined by the 3 auxologic indicators, alone or in combination, in the participating CF centres. When we considered any of the above-mentioned criteria, the rate of nutritional failure ranged between 15% and 34.6%, with no significant difference among centres (P = 0.65). This was also the case when using HAP<5th alone (mean value 12.2%, range among centres 5.7%-18.2%; P = 0.45) and WLP<10th alone (mean value 12.9%, range 0%-33.2%; P = 0.51), whereas a significant difference was observed by using BMIp <15th alone (mean value of 20.9%, range 0%-30.2%; P = 0.04). A significant difference among centres was also observed in the percentage of patients not fulfilling the new CFF nutritional goal: the percentage of patients with a BMIp<50th ranged between 37.4% and 78.3% (P < 0.01), with the majority of smaller centres being located on the right of the median value (Fig. 5).
DISCUSSION
We carried out a cross-sectional analysis to define growth status in a large cohort (892) of Italian patients with CF. We compared the anthropometric data of our patients with the US (CDC) charts and used 3 auxologic indicators: HAP, WLP, and BMIp. As recommended by the CFF, we did not use the IBW% because it has been shown to underestimate the severity of malnutrition in children with short stature and to overestimate the severity of malnutrition in children with tall stature (20).
Using the 3 anthropometric indicators the overall proportion of children with nutritional failure was 25.6%. The frequency of nutritional failure was higher when using the criterion of BMIp<15th (20.9%) rather than the HAP<5th (12.2%), whereas WLP<10th was observed for 12.9% of patients <2 years of age. The nutritional status of Italian patients with CF appears to be comparable to that reported in recent studies on American (7,14), German (15,21), and Scandinavian (22) CF populations. In all of these cohorts, including ours, mean values for the examined anthropometric parameters were lower than in the normal population. This finding clearly indicates that further improvement could be achieved in the nutritional status of patients with CF. In this perspective, the CFF has recently recommended to broaden the screening of malnutrition with the application of a new BMI goal (BMIp ≥ 50th) on the basis of its association with better lung function (16,20). Applying this BMI goal, the proportion of patients in our study with BMIp<50th was 54.4% compared with 56.8% recently obtained from the CFF patient registry (16).
Analysis of BMIp data showed that almost 70% of our patients aged 2 to 18 years have a normal nutritional status (>25th percentile); this percentage decreased to 59.8% using HAP, an index that is also applicable to patients aged 0 to 2 years.
A comparison of nutritional status among different studies is not feasible because they differ as regards type of parameter and the relative cutoff used to identify malnutrition. There is no consensus concerning the best index to be used for evaluating nutritional status in patients with CF. BMIp has recently been approved as the best parameter to assess weight-for-height proportion in patients older than age 2 years (14,15), and the 15th percentile has been reported to be a more appropriate cutoff point compared to the previously proposed 10th percentile (12). However, it has been argued that the weight-for-height indexes may significantly underestimate malnutrition (23) and, therefore, BMIp should not be used as a single indicator, but in combination with other indexes, such as HAP (12). This recommendation is further supported by our observation that BMIp and HAP resulted in different classifications of nutritional status in patients older than 2 years of age (Table 3). HAP indicated inadequate nutrition in a higher number of patients (324 vs 240), whereas BMIp detected more patients with nutritional failure (164 vs 93) and adequate nutrition (548 vs 464). However, a higher number of patients at risk for malnutrition were revealed by HAP (231 vs 76). Statistical analysis confirmed the disagreement between BMIp and HAP, with a low probability that both indexes would detect malnutrition in the same patient, whatever the cutoff percentile used (HAP and BMIp<25th: PPV 35.6%; HAP <5th and BMIp<15th: PPV 37.7%).
We observed similar features when we drew curves year by year (Figs. 2 and 3) to compare the sensitivity of HAP, WLP, and BMIp in relation to age. Although the reliability of curves depicting the age-related course of HAP, WLP, and BMIp may be limited by sample size, which in some age groups was limited (eg, none of the 13 patients aged 18 years had HAP<5th), HAP and WLP showed a similar trend over the first year of life, followed by a decline of HAP and an increase of WLP during the second year. This feature could be related to a more rapid improvement of length compared with weight in infants. As shown in Figure 2, BMIp<15th seems to be a more sensitive index than HAP<5th for defining malnutrition at all ages, particularly during pre-pubertal age and in patients older than 15 years. However, when we considered patients at risk for malnutrition (Fig. 3), the frequency of BMIp<25th was consistently lower than HAP<25th in patients aged 3 to 17 years, especially during adolescence, when there was the highest percentage of patients with HAP<25th (63.2% at 15 years, 54.8% at 17 years). This disagreement could be due to the high rate of short stature in patients with CF, particularly during adolescence. Therefore, an index on the basis of weight-for-height proportion, such as BMIp, may not be the most suitable for detecting malnutrition when stature is the most affected auxologic parameter. Our data confirm that BMIp<15th may not only be a good cutoff point to define nutritional failure but also indicate that it should preferably be used in association with other auxologic indexes such as HAP.
Another target of the present study was to identify the age groups at major risk of malnutrition. In our cohort the highest rate of malnutrition was observed during adolescence and this may be related to the high energy and nutrient requirement together with declining lung function.
In particular, malnourished patients were detected more frequently in the 14 to 18 years age group than in patients aged 10 to 14 years (P < 0.001), suggesting that close monitoring of nutritional status is equally important in adult patients with CF (20). These data substantially agree with those of Lai et al, who identified adolescents as one of the groups at higher risk of malnutrition (together with infants during the first year of life) (7). In our cohort, however, in the group of children aged 0 to 2 years, a significantly higher frequency of malnutrition was not observed, using both HAP<5th and HAP<25th. Because a neonatal screening program for CF was available in the majority of the participating centres (7/10), the more adequate nutritional status of Italian infants compared with other series (7) may be a reflection of the positive impact of neonatal screening in this patient population (24).
Identification of malnourished patients, particularly within the age groups at major risk of malnutrition, and subsequent aggressive nutritional intervention, are essential to prevent further deterioration in pulmonary disease and quality of life, and ultimately for survival.
We investigated the influence of several parameters such as sex, PI, MI, and FEV1 on nutritional status. As expected, the presence of PI negatively affected height, weight, and BMI, with a statistically significant relation with height and BMI (P = 0.03). There was a linear relation between FEV1 and nutrition (Fig. 5); a decreased lung function significantly affected all auxologic measures, and an inadequate nutritional status had a negative impact on the pulmonary status. Our cross-sectional data confirm the close relation between FEV1 and growth status, as already reported by several authors (25-27).
In our study, no gender differences were detected with regard to nutrition, suggesting that the gender gap described in CF, with a survival advantage for males (28-30), does not seem to be related to nutritional status in the Italian CF population. It is interesting to note that an inverse gender gap in nutritional status has been recently documented in Scandinavia (31). Similarly, MI was not found to affect the growth of Italian patients with CF; these data are in contrast to the results of Lai et al (32) but agree with other authors (33).
Finally, the data collected in this multicentre study enabled a comparison of nutritional outcomes among participating centres. A wide variability was documented in the nutritional outcomes among centres, suggesting that identification of best practice (learning from the best) or specific drawbacks in care centres may be used as a tool for quality improvement in CF care in Italy, as it has been recently reported from the United States and Germany (16,34).
One of the drawbacks of the present study is that we could not compare the anthropometric data of our patients with CF with those of a normal Italian reference population, which are not yet available. In addition, these data do not represent the whole Italian population because only one third of Italian CF centres took part in this study.
In conclusion, this is the first study on growth assessment in Italian patients with CF. Overall, we have observed that although more than half of the population is below the new BMI goal, nutritional status can be considered adequate (>25th percentile) in the majority of patients. However, nearly one third of the population could benefit from nutritional intervention and rehabilitation. We have also identified a higher risk of malnutrition between adolescents and young adults who, therefore, need closer surveillance.
This study represents also a first step towards a quality improvement project aimed at reducing variation in nutritional outcomes among reference CF centres and at identifying potential areas of intervention that may be the basis for additional studies.
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