Association between alternative healthy eating index (AHEI) with metabolic health status in adolescents with overweight and obesity

A sample of Iranian adolescents aged 12 to 18 were included in this cross-sectional survey conducted in 2020. Considering previously published study, about 62.2 percent of adolescents with extra weight suffer from MUO profile [22]. Therefore, with a precision (d) of 7%, power of 80%, and type I error of 0.05 (confidence interval (CI) of 95%), a sample size of 185 participants were required to be minimally sufficient. Applying a multi-level cluster sampling method, a total of sixteen schools in different regions of Isfahan were randomly selected. Then, according to the standard growth curve of age-sex-specific body mass index (BMI) percentiles [23], students who had overweight and obesity were only invited to participate in our investigation. However, students were not included in the study if they 1) had a history of inherited or metabolic disorders including type 1 diabetes, hypothyroidism and Cushing's syndrome; 2) took supplements or medications which probably affect their metabolic profile; 3) followed a specific weight loss diet. Totally, 203 adolescents with overweight and obesity including 101 boys and 102 girls were included in our study. Participants filled out written consent forms after receiving information about the study. Informed consents were also collected from the parents of the participants, as minors were participated in the study. The study protocol adhered to the ethical principles outlined in the 1975 Declaration of Helsinki. The Local Ethics Committee of the Isfahan University of Medical Sciences (IUMS) approved the study protocol (no. IR.MUI.RESEARCH.REC.1402.116).

We used a validated semi-quantitative food frequency questionnaire (FFQ) with 147 items to gather data on dietary intakes [24‐26]. This FFQ has been previously used to reflect the association between dietary intakes of Iranian youths and a variety of disorders [27, 28]. Therefore, this questionnaire has satisfactory validity and reliability among Iranian adolescents [29]. Based on this FFQ, participants have determined the frequency of consumption (based on daily, weekly or monthly) and also amount of each food item during the previous year. Then, the portion size of eaten food was converted to gram per day using household measurements [30]. Finally, Nutritionist IV software, which has been modified for Iranian foods, was used to measure the amount of calorie and nutrients intake.

AHEI-2010 consists of 11 components: fruits, vegetables, whole grains, nuts and legumes, long-chain n-3 fatty acids, polyunsaturated fatty acids (PUFA), red and processed meats, sugar-sweetened beverages and fruit juices, trans fatty acids, sodium and alcohol [17]. Due to a lack of relevant data in the current study, alcohol intake was excluded from the final score. AHEI-2010 was created by adjusting dietary intake of all components for total energy intake according to the residual approach [29]. Then, participants were divided into decile subgroups according to their energy-adjusted intakes of components. We utilized decile classifications as opposed to quantitative categories, since this approach would be less susceptible to misclassification. Individuals with the highest consumption of fruits, vegetables, whole grains, nuts and legumes, long-chain n-3 fatty acids and PUFA were given a score of 10 and those with the lowest consumption were scored 0. Conversely, other components including red and processed meats, sugar-sweetened beverages and fruit juices, trans fatty acids, and sodium were scored 0 in the highest consumption and 10 in the lowest consumption. The scores for the remaining deciles of these components were also allocated accordingly. The overall value of AHEI-2010 was determined by adding together the scores of all of these components, which ranged from 10 to 100.

An experienced nutritionist assessed standing height and weight using a stadiometer (to the closest 0.1 cm) and calibrated electronic scale (to the nearest 0.1 kg), respectively. All anthropometric measurements were done while participants were wearing no shoes and as little clothing as possible. Furthermore, we calculated BMI based on Quetelet formula (weight (kg)/ height² (m)) and categorized adolescents in terms of having overweight (85th < BMI < 95th percentile) or obesity (BMI > 95th percentile), according to World Health Organization (WHO) percentiles for age-sex-specific BMI [23]. Waist circumference (WC) measurement was taken to the nearest 0.1 cm, with a non-stretched, flexible tape after a typical expiration and with no external pressure applied. Blood pressure (BP) was measured while adolescents were sat on a chair with back supported and their feet were flat on the floor. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were assessed twice (after a 15-min break) by a mercury sphygmomanometer with a suitable cuff size, and the average BP was regarded in our analysis. Blood samples were taken from participants in a twelve-hour fasting state in the laboratory and then, blood samples were centrifuged at 3500 rpm within 10 min to separate the serum. Concentrations of fasting blood glucose (FBG), triglycerides (TG), high density lipoprotein cholesterol (HDL-c) and insulin were evaluated on the day of sampling, using glucose oxidase, glycerol phosphate oxidase, cholesterol oxidase, and electrochemiluminescence immunoassay methods, respectively. Homeostasis Model Assessment Insulin Resistance (HOMA-IR) formula was also applied to determine Insulin resistance (IR) [31]: [(fasting insulin (mU/L) × FBG (mmol/L)]/22.5.

Two different approaches were used to distinguish MHO and MUO phenotypes. In the first method, metabolic health status was determined based on the International Diabetes Federation (IDF) [32]. Such that, individuals were considered to be MUO if they had two or more of the following risk factors: 1) elevated FBG (≥ 100 mg/dL), 2) increased TG (≥ 150 mg/dL), 3) reduced HDL-c (< 40 mg/dL for the age of < 16 y, and < 50 mg/dL for girls/ < 40 mg/dL for boys in the ages of ≥ 16 y), 4) increased BP (≥ 130/85 mmHg). On the other hand, adolescents with less than two of mentioned items were recognized as MHO. In the second strategy, existence of IR was also assessed in addition to IDF [33]. Therefore, if participants had at least two items of IDF criteria and HOMA-IR scores ≥ 3.16, they were assumed to be MUO and those with HOMA-IR < 3.16 were considered a MHO.

Socioeconomic status (SES) of participants was assessed through a validated questionnaire including following items: parental education level, parental job, family size, having a personal room, traveling in a year, number of cars and laptops/computers in the family [34]. Data on age, gender, medications or supplements intake and history of diseases were also gathered using another self-administered questionnaire. A validated Physical Activity Questionnaire specified for Adolescents (PAQ-A) was applied to estimate physical activity (PA) level of participants [35]. This questionnaire includes nine items that evaluates usual and unusual activities of subjects over the previous week. By calculating total score, adolescents were categorized into four groups: sedentary (score < 2), low-active (3 < score ≤ 2), active (score ≥ 3), and very active (score ≥ 4). Due to the small number of sedentary and very active participants, we merged sedentary with low-active and active with very active to create two final categories: low level vs. high level.