Falls are one of the most frequent and serious problems facing older adults [1]. As this population increases rapidly, the number of fall related-injuries and deaths increases accordingly [2]. Falls are one of the leading causes of both fatal and non-fatal injuries among older people [3]. Approximately 30-40% of people over 65 years of age fall each year [4]. The frequency of falls increases with each decade beyond this threshold and approximately 20-30% of older adult fallers require hospitalization, assuming an increased risk of mortality [5,6]. About half of all fall-related injuries are minor but 5-10% of injurious falls result in fractures or head traumas [7]. Non-fatal fall related morbidity includes functional decline, loss of independence, and increased utilization of healthcare services [8]. Several underlying causes and risk factors for falls have been identified including gait and balance problems, visual impairments, muscle weakness, loss of physical and mental abilities and use of medications [9].
Gait and balance disorders are common in older adults and are a major cause of falls [10]. Postural balance and stability involve cooperation among the visual, proprioceptive and vestibular sensory systems and impairments in any of these systems can result in abnormal postural orientation leading to instability and/or dizziness [11]. Among these systems, proprioception provides sensory input from the peripheries to the central nervous system; therefore, it plays a critical role in maintaining optimal body alignment [12]. Various sensory receptors, such as Ruffini receptors and Pacinian corpuscles, are involved in delivering proprioceptive information to the central nervous system, and are most stimulated when the joint moves to its end range [13]. Muscle length changes caused by chronic poor posture can result in musculoskeletal misalignment including forward head posture (FHP) [13]. FHP is characterized as an extreme head anterior position in relation to a vertical reference line, which causes increased cervical spine lordosis, rounded shoulders and thoracic kyphosis [14]. FHP is associated with weakness of deep cervical short flexors and scapular retractor muscles, and shortening of upper and middle cervical extensors and pectoralis muscles [14,15]. The systemic review done by Singla and Vegar [16] addresses an important debate in postural alignment emphasizing coexistence of FHP, forward shoulder posture and increased thoracic kyphosis while their causative relation remains unclear. In another systematic review, Sheikhhoseini et al. [17] reported that exercise therapy programs may result in improvement of FHP. In a study on elite swimmers, Lynch et al. [15] reported successful application of strengthening and stretching exercises in reducing FHP and rounded shoulder posture (RSP) over the course of an 8-week exercise program. Shih et al. [18] compared the effect of exercise therapy with Kinesio taping on FHP. They reported that both exercise therapy including resisted — isometric chin-in while seated, isometric chin-in while seated, and upper trunk extension with chin-in while prone—and Kinesio taping demonstrated similar improvements in static posture, including forward head posture (FHP), when compared to the control group. However, enhancements in active range of motion of the cervical spine were observed solely in the exercise therapy group.
Head and cervical spine alignment have been shown to have a significant effect on postural stability. Kang et al. [19] examined the correlation between FHP and postural balance in computer-based workers. They found that workers with FHP had significantly lower equilibrium scores in condition 5 (unstable force platform and closed eyes) and 6 (unstable force platform and a moving screen with open eyes) on computerized dynamic posturography as compared to a control group [19]. However, Silva and Johnson [20] investigated young healthy participants’ balance during their natural head position compared to the same participants when asked to adopt an extreme FHP. The results showed that the sway area on the computerized stable platform was significantly larger when participants maintained their natural head position compared to adopting an extreme FHP [20]. To the best of our knowledge, there have been no studies investigating the effect of HEP and behavioral modification on upper quarter posture and postural instability in asymptomatic older adults with faulty upper quarter posture. Therefore, the purpose of this study was to investigate the effect of HEP on upper quarter posture and postural stability in older adults with faulty upper quarter posture. We followed CONSORT guidelines for reporting this study.
This study was a single group pretest-posttest design that was conducted in the physical therapy department at Loma Linda University between Winter 2022 and Spring 2023.
Twenty-one participants aged 65 to 79 years including fifteen females and six males were recruited for this study from the local community. Two female participants voluntarily dropped out of the study, leaving nineteen participants (13 females and 6 males) with mean±SD age of 72.7±3.4 years (Figure 1) who completed the study. All participants lived independently, did not require any assistive devices to walk, and were interested in improving their posture. Participants were excluded if they reported a history of chronic constant neck pain, balance impairments, vestibular impairments, diabetic peripheral neuropathy, or were taking medications causing dizziness. Moreover, participants who reported consistent daily intermittent neck pain more than 2/10 based on the Visual Analogue Scale (VAS) were also excluded [21]. The Physical Activity Readiness Questionnaire (2020 PAR-Q+) was used to screen participants for possible health risks associated with physical exertion. The Loma Linda University institutional review board approved the informed consent to guarantee the participants’ rights according to the Declaration of Helsinki.
Twenty-one participants aged 65 to 79 years were recruited for this study.
Participants received verbal and visual instruction on proper sitting and standing postural alignment. Moreover, participants were instructed to adopt proper sitting and standing posture with normal spine curvature as well as retracting their scapula and tucking their chin throughout their daily life [18]. Jull et al. [22] proposed two benefits of frequent upright postural correction. First, it may protect the cervical spine from overload pressure caused by misalignment of lumbar and thoracic spine as well as scapular position. Secondly, it may provide a re-education training for deep postural muscles concerning their stabilizing postural functions. They also recommended that postural correction needs to be implemented frequently by patients with emphasis on permanent change in their postural habits.
Several studies have shown that the combination of strengthening weak muscles and stretching tight muscles in people with FHP and RSP has significant effects on postural correction as well as reduction in neck and shoulder pain in different populations [14,17,18,22]. However, there is evidence reporting the benefits of individual exercise programs [23,24]. The combination of the exercises used in current study was based on these previous studies emphasizing strengthening the cervical deep flexors and scapula retractors in addition to postural behavioral modifications. Participants received illustrated HEP handouts. There were two strengthening exercises including chin tucks and scapular retraction. The chin tuck exercise started with participants leaning against a wall while keeping pelvis, shoulders and back of head in contact with wall. Participants were then instructed to tuck their chin by pulling the chin backward into the wall and hold for 10 seconds. The scapula retractor exercise started in the same position; however, their elbows were flexed 90 degrees to push against the wall while squeezing their scapulae together and maintain the position for 10 seconds. For progression at week five, participants were instructed to lay prone with a pillow under their chest, while holding arms at 90 degrees of shoulder abduction and elbow flexion. Participants then lifted their arms off the plinth by squeezing scapulae together and maintaining the position for 10 seconds. The HEP included 3 sets of 10 repetitions daily for 8 weeks [15].
The Bertec Computerized Dynamic Posturography (CDP) (Bertec corporation, Columbus, OH) was used to measure static postural stability. This tool calculates the center of gravity (COG) movement of the body using a sway-referenced force plate. Each condition was repeated three times with each trial being 20 seconds long. The system produces an equilibrium score reflecting participant ability to maintain COG within the theoretical limits of stability through various testing conditions [25]. The equilibrium score is the average COG sway of the three trials for each condition and is calculated on a 0 to 100 scale, where 100 represents optimal postural stability with no sway, and 0 represents no postural stability with highest degree of sway [25-28]. Participants were instructed to stand on the force plate with their feet aligned based on the system protocol and instructed to remain stationary during each trial while looking forward with their arms at their sides.
The Activities-Specific Balance Confidence Scale (ABC) measures balance confidence while performing daily activities [29,30]. The short version of the ABC scale (ABC-6) was used for this study and has been described for use in clinics and research settings. The ABC-6 is comprised of the 6 most balance-challenging items of the original ABC-16 and has good test-retest reliability (ICC=0.82) [31,32].
Thigpen et al. [33] described a screening procedure for forward head and rounded shoulder posture (FHRSP). They used participants’ profile picture in standing to measure forward head angle (FHA) and forward shoulder angle (FSA). Before taking a picture, they placed reflective markers on each participant’s C7, right tragus, and acromion. The FHA and FSA were then calculated using Adobe Photoshop (San Jose, CA, USA). The FHA is the angle between the line drawn from tragus to C7 markers and a vertical line passing through C7 marker. The FSA is the angle between same vertical line and the line drawn from C7 to acromion markers (Figure 2). Participants without FHRSP had FHA ≤36 degrees and FSA ≤22 degrees. Participants with FHRSP had FHA≥46 degrees and FSA≥52 degrees [33]. Therefore, we used the method described by Thigpen et al. to calculate FHA and considered 36 degrees or more as our cut-off angle to categorize our participants as normal posture or faulty posture.
The VAS was used to assess neck pain and consists of a 10-centimeter straight line, which is anchored by descriptions of “no pain/discomfort” at the left end and “worst pain/discomfort” at the right end of the line [34]. Participants were asked to mark a vertical line on the 10-centimeter straight line in accordance with the intensity of their neck pain [35].
The Neck Disability Index (NDI) measures the level of disability in people with neck pain and consists of 10 scaled questions regarding pain, concentration, and daily living activities [36]. Vernon and Mior [37] defined percentile range scores of NDI between 0 to 8 percent (none), 10 to 28 percent (mild), 30 to 48 percent (moderate), 50 to 68 percent (severe), and over 68 percent as complete disability. Furthermore, a good test-retest reliability (ICC 0.88; = [0.63 to 0.95]) has been reported for NDI in neck pain patients without upper extremity symptoms [38].
Participants read and signed the IRB approved informed consent document. Next, the participant’s profile picture was taken in self-selected sitting position without a back support to calculate FHA and FSA. The 2020 PARQ+ form was completed as a precaution for possible health risks associated with physical exertion. Next, participants completed the ABC-6, NDI, and VAS forms, then height and weight were measured. Static postural stability was then measured using the Bertec CDP. Lastly, participants received verbal and visual demonstration of the HEP and were asked to perform each exercise to demonstrate their understanding. In addition, participants were given an exercise log to track their daily HEP to turn it at the end of the study period. Participants received daily text message reminders for HEP and postural attention adherence. All the data in pre and post intervention assessment sessions were collected by two of the investigators of this study (M.K and M.J)
Data was analyzed using SPSS version 28.0. Assuming a moderate effect size of 0.6, a power of 0.80, an alpha of 0.05 and 15% dropout rate, the estimated sample size was 22 participants. Data was summarized using frequency (%) for gender, mean (standard deviation (SD)) for continuous variables, and median (minimum, maximum) when the distribution was not approximately normal. The normality of the outcome variables was examined using the Shapiro wilk test and boxplots. Changes in mean (SD) of body mass index (BMI), ABC-6, balance, FHA, and FSA over time (post versus pre)) were examined using paired t-test. The distribution of VAS and NDI scores was not approximately normal. Thus, changes in these scores over time were assessed using Wilcoxon signed rank test. The level of significance was set at p≤0.05.
Nineteen participants with a mean±SD age of 72.7±3.2 years, BMI of 24.7±3.6 kg/m2 completed the study. The majority of the participants were females (n =13, 68.4%). There was no significant difference in mean baseline variables between those who dropped out and those who completed the study (p>0.05). There was a significant decrease in median (min, max) NDI score over time (8 (0,14) versus 12 (2,24), p=0.020 (r=0.57)), however, there was no significant change in mean VAS score (p=0.72). In addition, there was a significant increase in mean ABC-6 scores over time (85.1±11.8 versus 76.3±18.4, p=0.02 (Cohen’s d=0.50; Table 1, Figure 3). When assessing changes in balance over time (post versus pre), there was a significant increase in the composite score of the balance (74.4±14.5 versus 71.4±14.2; p=0.006 (Cohen’s d=0.72; Figure 4). In addition, there was a significant decrease in mean FHA (48.3±8.4 versus 51.2±8.5; p=0.002 (Cohen’s d=0.85); Table1). However, there was no significant change in mean FSA over time (p=0.92).
The aim of this study was to investigate the effects of a HEP aimed at improving head and neck posture and static standing balance in community ambulating older adults. The results demonstrated significant improvements in forward head angle, however, forward shoulder angle did not change significantly. The results also demonstrated that balance significantly improved after the eight-week HEP. In addition, participants reported significant improvements in neck related function and postural confidence based on the NDI and ABC-6 questionnaire, respectively.
Standing balance in older adults continues to be problematic as the prevalence of falls in this group continues to increase [5,6]. Lee [39] reported that assessment of COG sway provides sensory inputs in accordance with environmental changes including change in ground stability or vision obscuring situations. Furthermore, when COG moves beyond its base of support (BOS), greater muscular activation is needed to return COG back within the BOS [40]. In addition, Ki and Song [41] reported that presence of faulty postural alignment including FHP, makes it more difficult to maintain COG within a BOS with sudden environmental changes due to decreased reaction timing of the motor control system.
In the current study, participants’ balance was challenged by exposing them to six different environmental conditions using a Bertec CDP system before and after completion of HEP. The results of this study support the findings of Lee [39] and Ki and Song [41]. Kang et al. [19] who also reported significant balance decrease in people with FHP compared to normal participants in conditions 5 and 6 using a similar Bertec system. Moreover, the results of the current study are consistent with results reported by Lynch et al. [15] and Shih et al. [18] regarding improvement in FHA following exercise therapy.
In addition, improvements in the current study pertaining to FHA after completing the HEP agree with a systematic review by Sheikhhoseini et al. [17] where researchers indicated that exercise therapy programs may result in improvement of FHP. Buttagat et al. [42] also reported significant improvement in FHA in participants with FHP following combination of three different therapeutic methods including traditional Thai massage, scapular stabilization exercise, and chest mobilization. However, by including different therapeutic methods, the authors were unable to determine which of therapeutic method had the greatest effect on improving in FHA.
The results of the current study were not in agreement with Silva and Johnson [20], who reported significant increase in sway area with normal healthy posture in compared to when they had them adopt an extreme FHP. However, their participants did not have an actual chronic postural misalignment affecting their motor control system. Furthermore, imposing an abnormal posture to a healthy body may elicit more muscular activation while trying to recover the posture to the normal status, in accordance with Shumway-Cook and Woollacott [40].
A limitation in the current study was the age range of our participants and length of data collection sessions because fatigue likely factored into the performance; however, all participants were exposed to the same procedure. Further research is needed to confirm the effect of upper quarter alignment in postural stability as well as the role of exercise therapy to restore faulty posture in this body region.
Head and neck HEP demonstrated improved FHA and postural stability in older adults with faulty upper quarter posture and postural instability. This simple, yet effective HEP should be considered for this population.
The authors thank the Loma Linda University PhD in Physical Therapy Program for supporting this research.
The author of this paper has no financial relevancy and interest to the content of the research expressed in this study.
Mean ± SD for Changes in Outcome Variables over Time (N=19)
Variable | Pre | Post | Mean difference (95% CI) | P-value (Cohen’s d) |
---|---|---|---|---|
BMI (kg/m2) | 24.7±3.6 | 24.8±3.7 | 0.063 (0.46)† | |
VAS (mm) | 1 (0,16)* | 0.0 (0.0,4.4) | 0.720 (0.08) | |
NDI (%) | 12 (2, 24) | 8 (0,14) | 0.020 (0.57) | |
ABC-6 (%) | 76.3±18.4 | 85.1±11.8 | 8.8 (-0.3, 18.0) | 0.029 (0.50) |
Balance | 71.414.2 | 74.414.5 | -3.0 (-5.0, -1.0) | 0.006 (0.72) |
FHA (°) | 51.28.5 | 48.38.4 | 2.9 (1.3, 4.6) | 0.002 (0.85) |
FSA (°) | 31.414.3 | 31.115.3 | 0.3 (-6.2, 6.8) | 0.921(0.23) |
Note, BMI=Body Mass Index, VAS=Visual Analogue Scale, NDI=Neck Disability Index Scale,
ABC-6=Activities-Specific Balance Confidence Scale, FHA=Forward Head Angle, FSA=Forward Shoulder Angle.
*Median (Minimum, Maximum); †Effect Size for Wilcoxon Signed Rank Test