5.1.1 Dentofacial and pharyngeal morphology
Dentofacial and pharyngeal morphology were clinically evaluated by a standard orthodontic screening method by one experienced orthodontist (T.I.). The occlusion was assessed according to the modified method of Björk (Björk et al. 1964) in the intercuspal position. The recorded variables included molar occlusion (distal, normal or mesial), overjet (mm), overbite (mm), crowding ( 2 mm), spacing ( 2 mm), anterior and lateral open bite ( 2 mm) as well as cross bite and scissors bite. In cross bite, one or more lower posterior teeth are buccal to the upper counterpart(s), while in scissors bite, the whole occlusal surface of the upper posterior teeth is buccal to that of the lower antagonistic teeth. The shape of the palate was visually defined as wide, normal or narrow. The existence of adipose tissue under the chin was assessed visually. Facial profile (convexity, concavity and vertical dimension) was also assessed visually. To assess the actual airway between the tonsils the children were asked to breathe through their nose, which then relaxes the pharynx and palatal area. The tonsils were considered hypertrophied if there was 1 cm or less space between the tonsils.
The definition corresponds to classes 3-4 of the Brodsky classification (Brodsky 1989). Soft palatal morphology was classified according to the Mallampati Classification, which is based on clinical examination with maximal mouth opening and tongue protrusion in the seated position (Mallampati et al. 1985). Dominant mouth breathing was assessed visually during the clinical examination. Previous or ongoing orthodontic treatment was checked from the child´s dental records and classified according to the most prevalent treatment modalities in Finnish children among the studied age groups: Quad helix, head gear, or other (mostly eruption guidance appliance). Noteworthy, if an examination showed treatment need, a child was referred to an appropriate professional (i.e., dentist, orthodontist, physician).
5.1.2 Sleep
Sleep, SDB and associated factors were assessed by a questionnaire. The questions in the sleep questionnaire used were based on an established Finnish questionnaire that have been used to screen for sleep disturbances and SDB (Partinen and Gislason 1995). The parents filled out the questions regarding the child’s quantity and quality of sleep, symptoms of SDB, frequency of upper airway infections and previous operative treatments, such as ATE.
Unfortunately, the parents did not reliably remember their child`s possible ATE, so this important data could not be used in the present study. SDB was defined as witnessed breathing pauses (apneas) (sometimes, usually or always/almost always) and/or frequent (most of the sleeping time or frequently) and/or loud (quite loudly, loudly or extremely loudly) snoring and/or nocturnal mouth breathing (usually or always/almost always) observed by the parents. In other words, if the child had one or more of above-mentioned symptoms, he/she was defined as having SDB.
Sleep duration was assessed using a combined heart rate and movement sensor (Actiheart,
electrocardiogram electrodes (Bio Protech Inc., Munmak-eup, South Korea) that were placed on the child’s chest in a standardized manner (Brage et al. 2005). Children were asked to wear the Actiheart device continuously for at least four consecutive days that included two weekdays and two weekend days. The duration of sleep was evaluated over an average of 4.1 nights and analyzed manually from the heart rate and movement data by one exercise specialist and confirmed by one physician, if needed. Falling asleep was defined as the time point when the accelerometer counts had reached zero and the heart rate had settled down for at least five minutes. Waking up was defined as the time point when the accelerometer counts and heart rate had increased continuously from zero. Sleep duration was calculated as the time between these two time points.
5.1.3 Body composition and fitness
Body height was measured with head position being in the Frankfurt plane without shoes by a wall-mounted stadiometer with an accuracy of 1 mm. Body weight was measured by the bioimpedance method using the Inbody 720® device (Biospace Co. Ltd., Seoul, Korea) with an accuracy of 100 g. Both parameters were measured after an overnight fast. BMI was calculated as weight (kg) divided by height (m) squared. Z-scores for height, weight and BMI were assessed with an obesity calculator that uses age- and sex-specific British growth reference data from 1990 (Cole et al. 1995). BMI-SDS was calculated using Finnish growth references (Saari et al. 2011). Overweight and obesity were defined using the age- and sex-specific BMI cut-offs derived from growth curves corresponding to BMI values 25 and 30 in adults 18 years of age, published by the International Obesity Task Force (IOTF) (Cole et al.
2000). Body fat percentage was assessed by the dual-energy x-ray absorptiometry (DXA) method using the Lunar® device (Lunar Prodigy Advance, GE Healthcare, Madison, Wisconsin, USA) in the afternoon in the non-fasting state. The cardiorespiratory fitness of the children was tested with an electromagnetic cycle ergometer with a pediatric saddle module (Ergoselect 200 K, Ergoline, Bitz, Germany) as previously described in detail (Lintu et al.
2014).
5.1.4 Photograph
A standardized method was used for photographing the participants. The photos were taken using a Canon EOS 300D® digital camera in the lateral projection of the face at a distance of two meters. The children were standing in a natural head position (NHP) in front of a mirror with a little bubble level taped on their temple to control the correct head position.
The paper prints of the photos were gathered into a folder and a short instruction guide along with the profile figures was formulated. The folder was examined first by a reference orthodontist (T.I.) and then by seven other healthcare professionals who work with children, i.e., another orthodontist, a dentist with extensive orthodontic experience, a general dental practitioner, an otorhinolaryngologist, a pediatrician, an oral hygienist and a public health nurse. In addition, a dental student examined the folder. The observers classified the profiles visually as normal/mildly convex, clearly convex or straight/concave based on three model pictures (Figure 4).
Figure 4. Formula of normal/mildly convex, evidently convex and straight/concave profiles and instructions to the observers
The photographic data was digitized and analyzed by Wincepht® 8.0 software in order to analyze the profiles more objectively and further, to compare the subjective and objective assessment. Soft tissue landmarks Glabella (G`), Subnasale (Sn) and Pogonion (Pg`) were digitally identified to calculate the angle G`- Sn - Pg` indicating the angle of facial convexity (Legan and Burstone 1980). Furthermore, soft tissue Nasion (Na`) and soft tissue Menton (Me`) were identified for the purpose of analyzing the reliability of the measurement of the vertical proportions (Sn`-Me`/Na`-Me`) of the face (Figure 5).
Figure 5. Digitized soft tissue landmarks on lateral facial photographs. Soft tissue Glabella (G`), Subnasale (Sn), Soft tissue Pogonion (Pg`), soft tissue Nasion (Na`) and soft tissue Menton (Me`)
5.1.5 Well-being measurements
The parents completed the questionnaire concerning the child`s well-being during the previous three months. The questionnaire was developed by the PANIC-researchers to assess the most important components of well-being in general populations of children. The questionnaire was not validated or piloted, but the Cronbach´s Alpha analysis showed high internal consistencies for the psychological well-being score (Cronbach’s Alpha 0.91), the physical well-being score (Cronbach’s Alpha 0.83) and the social well-being score (Cronbach’s Alpha 0.76). The questionnaire had three parts: 1) psychological well-being, 2) physical well-being and 3) social well-being. Altogether 19 items were used to inquire about psychological well-being (i.e., timidity, tearfulness, insecurity, anxiety, frustration, depression, restlessness, squeamishness or anger, aggressiveness, difficulties in concentration, problems in concentration with homework, difficulties with homework, unwillingness go to school, troublemaking in class, discouragement, feeling of inferiority, forgetting things, sleeping difficulties, difficulties in reaching the age-appropriate level in doing things). Physical well-being was inquired with 12 items (i.e., problems with the following activities: sitting, standing, walking, running, lifting or carrying things, eating or drinking, washing, dressing up, performing housework as well as experiences of physical pain, physical tiredness, difficulties in reaching the age-appropriate level in doing things).
Social well-being was inquired with 6 items, (i.e., difficulties getting along with other children, being bullied, arguing with other children, bullying other children, lack of interest in hobbies, difficulties in reaching the age-appropriate level in doing things). Each item was rated on a 5-point scale (0=not at all, 1=once or twice in three months, 2=sometimes, 3=often, 4= every day or almost every day). The total well-being scores from the questionnaire indicate the status of physical well-being (range of possible score 0-48), psychological well-being (range of possible score 0-76) and social well-being (range of possible score 0-24).
5.1.6 Physical activity and inactivity
The assessments of the physical activity and sedentary activities were recorded during a usual week – on five week days and two weekend days (Väistö et al. 2014). Parents were asked for information on regular physical activity, unstructured activity, physical education, physical activity at school and while commuting to and from school and during recess by the PANIC Physical Activity Questionnaire. The total amount of physical activity was calculated as minutes per day. Habitual sedentary activity was also assessed by the same questionnaire.
The amount of total sedentary activity was calculated by summing the time spent on each sedentary activity type and was expressed as minutes per day weighted by the number of weekdays and weekend days. Media use was calculated by summing up watching television and videos, using a computer, playing video games, using a mobile phone and playing mobile games and reported as minutes per day. The questionnaire was validated by Actiheart monitoring (Väistö et al. 2014).
5.1.7 Dietary assessments
Food consumption and nutrient intake were assessed by food records administered by the parents on four predefined consecutive days, as described previously (Eloranta et al. 2012).
The food records were reviewed by a clinical nutritionist and analyzed using The Micro
Nutrica® dietary analysis software, Version 2.5 (The Social Insurance Institution of Finland).
The Dietary Approach to Stop Hypertension (DASH) Score was used as an indicator of a healthy diet and calculated as described previously (Fung et al. 2008). The DASH is a commonly used dietary quality index, which was originally developed for treatment of hypertension in adults, but is also commonly used in children (Moore et al. 2005). In brief, the intake of seven food and nutrient groups, including fruit and fruit juices, vegetables, high-fiber ( 5%) grain products, low-fat (<1%) milk and sour milk products, red meat and sausage, sugar-sweetened beverages and sodium, were categorized into quintiles and scored from 1 to 5. The highest quintile achieved the maximum score of 5 and the lowest quintile achieved the minimum score of 1. Reverse scoring was applied for red meat and sausages, sugar-sweetened beverages and sodium. The resulting 7 component scores were summed to create the overall DASH Score. A higher score indicates a higher dietary quality.
5.1.8 Socioeconomic background and characteristics of the parents
The characteristics of the parents were reported with a structured questionnaire from both mother and father. Parental socioeconomic status was assessed by the highest educational level in the family. Parents selected the appropriate level from three education categories:
vocational, polytechnic and university. The total annual income of the households was encoded into three categories (<€30,000/year, €30,001-€60,000/year and >€60,000/year).
Possible unemployment, daily smoking and alcohol consumption (portions/week) were reported.