Subjects
Forty-five well-trained female athletes with menstrual disorders (18 rowers, 12 synchronized swimmers, 15 triathlonists) were recruited from different sports club in Poznań and thirty-one the (12 rowers, 8 synchronized swimmers, 11 triathlonists) completed a dietary intervention. The inclusion criteria were: menstrual irregularity within the last 12 months, a training period of at least 3 years, training session > 4/wk, no serious medical conditions, no use of hormonal contraception or other medications that might interfere with the hypothalamic-pituitary-gonadal axis activity, no clinical diagnosis of an eating disorders, no history of clinical diagnosis of primary ovarian failure, hyperprolactinemia, thyroid dysfunction or polycystic ovary syndrome and non-smoking.
Written informed consent was obtained from all participants or their parents. The study was approved by the Poznań Medical Ethics Committee (no. 334/09).
Menstrual status
Each subject completed a two-part medical questionnaire. The questions in the first part concerned menstruation: age at menarche, length of the menstrual cycles, and history of amenorrhea. Part two of the questionnaire referred to sport activities: age at the beginning of training, training period, number of training session per week, hours of training per day and per week.
Primary amenorrhea was diagnosed where there was no onset of menses by 15 years, while secondary amenorrhea was diagnosed when there was no menstruation for 6 months, or for more than three times the previous cycle length. Menstrual periods that occurred more than 35 days apart were described as oligomenorrhea [10].
Each participant underwent gynecological evaluation, including a pelvic ultrasound and measurements of luteinizing hormone (LH), follicle-stimulating hormone (FSH), progesterone (P), 17β - estradiol (E2), prolactin (PRL), thyroid-stimulating hormone (TSH), testosterone (T), and sex-hormone-binding globulin (SHBG) serum concentration, in order to exclude independent causes of amenorrhea or oligomenorrhea (such as pregnancy, primary ovarian failure, hyperprolactinemia, thyroid dysfunction or polycystic ovary syndrome).
Blood sampling and biochemical analyses
Blood samples were obtained in menstruating subjects between days 2 and 5 of the menstrual cycle (in the early follicular phase), and at random in amenorrheic subjects. Blood serum samples were taken between 6.00 a.m. and 9.00 a.m. following overnight fasting and rest. The athletes were instructed to abstain from caffeine and alcohol for 24 hours prior to the blood sampling, and to refrain from performing strenuous exercise on the day of sampling.
Serum concentration of LH, FSH, E2, P, PRL, TSH, T and SHBG were measured by immunochemical methods using Chemiluminescent Microparticle Immunoassay (CMIA) and Microparticle Chemiflex Flexible interassay protocols and making use of diagnostic sets and an ARCHITECT automatic analyzer. Serum leptin levels were estimated using Human Leptin Elisa by LINCO Research. All hormones concentrations were determined in duplicated.
Body weight and body composition measurements
In order to evaluate the nutritional status, the anthropometrical indices, height and weight were measured using an anthropometer coupled with a WPT 200 OC verified medical scale (Rad Wag). BMI (kg/m2) was calculated as body weight divided by squared body height. The participants were dressed in minimal clothing during the measurements, which were rounded to the nearest 0.5 kg and 0.5 cm. Analysis of body fat mass (FM) and fat-free mass (FFM) was performed in the morning, following an overnight fast, with the subjects lying in a supine position, using BODYSTAT 1500, as described by Heyward et al. [11].
Resting metabolic rate
Resting metabolic rate (RMR) was assessed by using a portable indirect calorimeter for 25 minutes (Cosmed K4b2, Cosmed, Italy). A face mask (Hans Rudolph, Kansas City, MO) covering the mouth and nose of the participant was attached to a bidirectional digital turbine flow-meter and fastened to the participant using a mesh hairnet with Velcro straps. To guarantee an airtight seal, a disposable gel seal (Hans Rudolph) was positioned between the inside of the face mask and the skin. The Cosmed K4b2 system was calibrated prior to each individual test according to the manufacturer’s guidelines. Breath-by-breath O2 and CO2 gas exchange was measured and recorded in the portable unit’s computer system. On completion of each test, the stored data were transferred to the Cosmed K4b2 version 6 computer software running on a Windows-based laptop computer. The data were then averaged over 15 second intervals and transferred to Microsoft Excel for further analysis. The morning before the RMR measurements, the Cosmed K4b2 was calibrated with a calibration gas mixture (16% O2, 5% CO2). The test was carried out with the participant in a comfortable supine position, at an environmental temperature of 21–22°C. All measurements were done in the morning (between 6 and 9 a.m.) following a 12 hours fast and a minimum of 8 hours of rest. The results of the RMR measurement were compared with the RMR predicted by the Harris-Benedict equation [12] and the RMR(kcal)/FFM(kg) ratio was also calculated.
Energy and nutrients intake
Seven consecutive days of dietary records were obtained under the supervision of dieticians. Athletes had a regularly contact with registered dietitian who teach them and control how to record nutrition intake. All meals (including recipes and item masses), nonmeal foods, beverages, and fluids were recorded in diary form using a photographic album of dishes [13]. The daily diets were analyzed for their energy and nutrient levels (fat, protein, carbohydrate, dietary fiber, calcium, phosphorus, iron, zinc, vitamins A, D, B1, B2, niacin, B6, B12, foliate and vitamin C) using the Dietician computer software package, based on Polish food composition tables [14].
Total energy expenditure and energy availability
For three days, each subject wore a heart-rate monitor (HR) (Polar Sport Tester, RS 400, Finland) in order to estimate total energy expenditure (TEE). For each subject, the relationship between HR and VO2 was established. The measurements were carried out two or more hours after meals, and after the subject had rested for 30 min, having arriving at the laboratory. Results were obtained by simultaneous measurement of HR and VO2 for the following activities carried out sequentially: lying in supine position, sitting quietly, standing quietly, and continuous graded exercise on a cycle ergometer. After preliminary editing to remove spurious HR data, the total energy expenditure (TEE) was calculated using the Flex-HR method. This method requires the definition of a Flex-HR for each subject, above which there is a good correlation between HR and VO2, but below which there is a poor correspondence between the two parameters. The Flex-HR was calculated as the mean of the highest HR for the resting activities (supine, sitting, and standing) and the lowest HR of the exercise activities. At the end of the measurement session, researchers transferred the minute-by-minute records of the last twenty-four hours from the instrument to a database. The 24-hour energy balance (EB) was calculated as the difference between the means of seven consecutive days of 24-hour energy intake and the TEE as a mean of three days. Energy availability (EA) was calculated by subtracting exercise energy expenditure (EEE) from total daily energy intake, and was adjusted for FFM kg [10].
Dietary intervention
After the evaluation of the participants’ nutritional habits, all the athletes were informed of nutritional mistakes in their current diets and of the health consequences of dietary deficiencies. Then, for each of the athletes who was qualified for the study, we prepared an individual diet. Taking into account the energy balance and the energy availability, the daily energy intake was established on the basis of the individual energy requirements that had been calculated from the total energy expenditure data. The recommended level of protein intake was determined in accordance with the recommendations of the American College of Sports Medicine Female Athlete Triad Position Stand (ACSM) [10], taking into account 1.2–1.6 g/kg/d intake. Using the recommendations of Manore et al. [15], the level of carbohydrates and fat intake was determined, which respectively amounted to a minimum of 55% and 25–30% of the daily energy intake. Adequate daily intake for calcium (1000–1300 mg) and vitamin D (400–800 IU or 10–20 mcg) are based on the ACSM recommendations [10] and on Roupas et al. [16] results. The recommended intake of other vitamins and minerals was established in accordance with Recommended Dietary Allowances for girls aged 16–18 years and women over 19 years, in accordance with Jarosz et al. [17]. The dietary counseling session also included a discussion of special foods for athletes, sports drink, supplements, shopping tips, low-fat and low-calorie food, food preparation, dining out, iron, calcium and vitamins in foods. After first and second month of nonpharmacological dietary intervention, the control of following dietary intervention was conducted. Repeated assessments of total energy expenditure (1 day), energy availability, and the energy and nutrient values of daily diets (3 days) were conducted (data no shown). After third month the control of effect of dietary intervention was conducted and then total energy expenditure (3 day), energy availability, and the energy and nutrient values of the athlete’s daily diets (7 days), LH, FSH, E2 and P serum concentration were repeated by measured. To statistical analysis we used data from baseline of study and after third month of dietary intervention.
Statistical analysis
Means and standard deviations of the quantitative variables were calculated. The normality of the distribution was checked. Comparisons between data from before and after the three-month dietary intervention were carried out using a t-test for independent variables. Connection between energy availability and LH serum concentration were carried out using Spearman’s rank correlation test. Statistical analyses were performed using Statistica 8.0 software (StatSoft, 2008). P-values of less than 0.05 were considered statistically significant.