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Childhood obesity is increasing globally. Primary care doctors are well-positioned to identify children with obesity. This study aimed to assess the usage of clinical practice guidelines (CPG) to determine obesity and the knowledge of primary care doctors regarding childhood obesity.
Methods
An online survey was conducted between November 2023 and February 2024 among primary care doctors in Klang Valley, Malaysia. The questions assessed doctors’ knowledge, practices, beliefs, and usage of the CPG in managing childhood obesity.
Results
There were 246 participants during the study period. Among the doctors, 101 (41%) knew the correct definition of “childhood overweight” while 120 (49%) doctors used the CPG. Doctors using the CPG had higher odds of knowing the correct management (odds ratio [OR], 2.65; 95% confidence interval [CI], 1.30–5.41; P=0.006). Doctors using the CPG had higher odds of screening for childhood obesity complications and measuring body mass index (BMI), blood pressure, and pubertal status. Multivariate analysis showed that doctors working in government clinics (OR, 3.56; 95% CI, 2.01–6.32; P<0.001), having postgraduate training (OR, 3.95; 95% CI, 2.08–7.51; P<0.001) and having worked less than 5 years (OR, 4.53; 95% CI, 1.85–11.08; P<0.001) had higher odds of using the CPG. Doctors working in government clinics (OR, 5.93; 95% CI, 1.95–18.05; P=0.002) and used the CPG (OR, 7.26; 95% CI, 2.09–25.27; P=0.002) had higher odds of measuring the BMI.
Conclusion
Knowledge regarding diagnosis and management of childhood obesity among primary care doctors is still lacking. CPG on childhood obesity could be a useful tool for improving the diagnosis, management, and screening of childhood obesity.
The prevalence of childhood obesity is rising worldwide. This trend has been observed in many countries, such as Korea (8.7% in 2007 to 15.0% in 2017), Brazil (6.5% in the 1990s to 12.0% in the 2010s), the United States (16.9% in 2011 to 19.7% in 2020), and China (15.5% in 2010 to 29.4% in 2022) [1-4]. In Malaysia, childhood obesity has almost doubled from 8.4% in 1996 to 14.5% in 2022, and this upward trend has led to significant health and economic impacts on individuals, populations, and the country [5]. At the individual level, childhood obesity is linked to many medical and socioemotional consequences, including type 2 diabetes, sleep apnea, menstrual abnormalities, hypertension, psychosocial problems, hypercholesterolemia, and fatty liver disease [6].
To circumvent this problem, early disease detection may improve the management of childhood obesity. As primary healthcare is the first point of contact between children and the healthcare system, primary care doctors are strategically placed to identify children with obesity. However, evidence shows that some primary care doctors are not well equipped to manage childhood obesity [7,8].
The Malaysian clinical practice guidelines (CPG) for obesity were first introduced in 2004, and the second edition was published in 2023 [9]. Its contents cover the diagnosis, clinical evaluation, prevention, and management of childhood and adolescent obesity. Although strategies for the implementation and quality of the CPGs are well-documented, studies reporting the benefits of using CPG on improving outcomes remain scarce [10,11]. A systematic review revealed that certain guidelines led to improvements in the quality of care, whereas others showed negative results [12].
Therefore, this study aimed to describe usage of the CPG for obesity among primary care doctors and their knowledge regarding childhood obesity. Any identified shortfalls can then be targeted and improved.
Methods
This cross-sectional study was conducted between November 2023 and February 2024 among primary care doctors in the Klang Valley region of Malaysia via an online survey. This study was approved by the Medical Research and Ethics Committee of the Ministry of Health, Malaysia (NMRR ID-23-02962-DUK) and the Research Ethics Committee of the National University of Malaysia (HTM-2023-030).
In Malaysia, primary healthcare is provided by both government health and private clinics. Government health clinics follow standardized operating procedures, whereas private clinics follow individualized procedures established by a private clinic doctor who owns the clinic. Doctors from both government health clinics and private clinics were included in this study. They had to be proficient in English and able to fill out Google Forms questionnaires. Pediatricians working in private clinics were excluded.
There was a total of five districts involved in the study. The district health office for each district was contacted for assistance with recruitment. Quota sampling was performed to select the government health clinic doctors. Each district health officer sent messages to 30 government health clinic doctors; 128 doctors responded, with a response rate of 85.3%.
For doctors working in private clinics, the Malaysian Medical Association (MMA) was contacted. E-mail invitations were sent to all private clinic doctors registered under the MMA. A total of 5,000 emails were sent; 118 responded, a response rate of 2.36%.
The messages and emails contained a Google Forms link that the participants answered. Google Forms questions were based on a study by Siversten et al. [13] in 2008, and the content was validated by two pediatric endocrinologists. There were 14 questions from three sections.
The first section involved demographic data, including place of practice, sex, work experience, postgraduate experience, and the number of pediatric patients seen each day. The second section comprised the doctor’s knowledge of the diagnostic criteria for childhood overweight, whether the doctor had ever diagnosed a child as being overweight, and their usual practices. The practice component included questions on regular monitoring (height, weight, body mass index [BMI], waist circumference, pubertal changes, and waist circumference), management of obesity, and screening for complications if participants had ever diagnosed a child with overweight (type 2 diabetes, hypercholesterolemia, fatty liver, hypertension, sleep apnea, menstrual abnormality, and psychosocial issues). The third section investigated the doctors’ beliefs about childhood obesity.
Doctors were considered to have postgraduate training in family medicine if they had the qualifications of member of the Academy of Family Physicians or International Conjoint Fellowship of the Royal Australian College of General Practitioners under the Academy of Family Physicians or master of medicine) in family medicine. Correct intervention was defined as choosing all three management choices: dietary change, change in exercise, and familial behavioral change.
Statistical analysis
The sample size was calculated based on the formula by Daniel [14], using a 95% confidence level and 5% precision. According to Sivertsen et al. [13], the prevalence of CPG use was 28.5%. The required sample size was 313.
Data were analyzed using the IBM SPSS ver. 28.0 (IBM Corp.). Categorical data were described using frequencies and percentages. Statistical analysis was conducted using the chi-square test and Fisher exact test and reported as odds ratio (OR) and 95% confidence interval (CI). For the analysis of management and screening, participants who had never been diagnosed with childhood obesity were excluded because the questions were based on whether the doctor had ever diagnosed a child with obesity, leaving 200 participants in the analysis. Multivariate analysis using logistic regression with a forward stepwise (likelihood ratio) was conducted on the factors associated with the doctor’s usage of the CPG based on the doctor’s characteristics, namely, place of practice, sex, work experience, postgraduate experience, and number of pediatric patients seen each day. Multivariate analysis of factors associated with the practice of measuring BMI, providing the correct intervention for childhood obesity, and screening for type 2 diabetes mellitus was conducted based on the doctor’s characteristics and usage of the CPG. Statistical significance was set at P<0.05.
Results
This study involved 246 doctors, with an overall response rate of 4.8%. Most respondents were female, had more than 10 years of work experience, did not have postgraduate training, and saw two or more pediatric patients per day (Table 1).
Of the doctors in the study, 101 (41%) provided the correct definition of childhood overweight as being more than the 85th percentile on the BMI chart according to age and sex. Approximately half of the doctors (120) used the CPG for managing childhood obesity. Doctors from government health clinics had higher odds of giving the correct definition of childhood overweight (OR, 2.52; 95% CI, 1.49–4.27; P<0.001), ever diagnosed childhood obesity (OR, 3.03; 95% CI, 1.52–6.03; P=0.001), and followed the CPG (OR, 3.03; 95% CI, 1.80–5.09; P<0.001).
Regardless of their understanding of childhood overweight, most doctors in primary healthcare clinics perform basic measurements regularly or only when clinically indicated (Table 2).
Among the doctors, 46 (18.7%) mentioned that they had never diagnosed children with overweight or obesity. Of the remaining 200 doctors, 158 (79%) provided the correct intervention. More than half the participants screened overweight children for type 2 diabetes mellitus (n=143; 71.5%), sleep apnea (n=128; 64.0%), hypertension (n=120; 60.0%), psychosocial problems (n=120; 60.0%), and menstrual problems (n=107; 53.5%). Less than half the participants would screen for hypercholesterolemia (n=98; 49.0%), fatty liver disease (n=74; 37.0%), or orthopedic problems (n=73; 36.5%).
Most doctors agreed with the statement that childhood obesity is a significant problem (98.8%), childhood obesity is a strong predictor of future adult obesity (94.4%), and that childhood obesity leads to health complications (99.6%). The doctors agreed that there is a role for primary healthcare providers in preventing childhood obesity (97.1%) and that they felt comfortable raising the issue of childhood obesity with their parents (87.5%). Almost all the doctors (94.3%) were interested in learning more about childhood obesity management.
Government doctors had higher odds of measuring height (OR, 5.83; 95% CI, 1.25–27.20; P=0.012), BMI (OR, 8.33; 95% CI, 2.80 to 24.77; P<0.001), waist circumference (OR, 1.95; 95% CI, 1.15–3.31; P=0.013), blood pressure (OR, 11.78; 95% CI, 3.46–40.09; P<0.001) and pubertal status (OR, 1.98; 95% CI, 1.07–3.67; P=0.029). Government doctors had higher odds of screening for complications such as type 2 diabetes mellitus (OR, 2.11; 95% CI, 1.13–3.93; P=0.018), hypercholesterolemia (OR, 2.76; 95% CI, 1.55–4.93; P<0.001), fatty liver (OR, 2.22; 95% CI, 1.21–4.06; P=0.009), hypertension (OR, 3.24; 95% CI, 1.79–5.84; P<0.001) and sleep apnea (OR, 2.44; 95% CI, 1.35–4.41; P=0.003). Government doctors also reported higher odds of providing the correct definition of childhood overweight and obesity (OR, 2.52; 95% CI, 1.49–4.27; P<0.001). Government doctors (OR, 3.03; 95% CI, 1.80–5.09; P<0.001) and doctors with postgraduate training (OR, 3.53; 95% CI, 1.94–6.45; P<0.001) had higher odds of using the CPG.
Use of the CPG had no significant effect on providing the correct definition of childhood overweight (OR, 1.20; 95% CI, 0.72–2.00; P=0.479). Doctors who used the CPG had higher odds of having previously diagnosed childhood overweight or obesity (OR, 2.03; 95% CI, 1.04–3.96; P=0.035) and having the correct management (OR, 2.65; 95% CI, 1.30–5.41; P=0.006). Usage of the CPG was associated with higher odds of measuring BMI, waist circumference, blood pressure, and pubertal status (Table 3). Doctors who used the CPG also had higher odds of screening for complications.
Multivariate analysis identified several factors that were significantly associated with usage of the CPG, namely working in government clinic (OR, 3.56; 95% CI, 2.01–6.32; P<0.001), having postgraduate training (OR, 3.95; 95% CI, 2.08–7.51; P<0.001), and having worked for less than 5 years (OR, 4.53; 95% CI, 1.85–11.08; P<0.001). In terms of the practice of measuring BMI, significant associations were found with working in government clinics (OR, 5.93; 95% CI, 1.95–18.05; P=0.002) and usage of the CPG (OR, 7.27; 95% CI, 2.09–25.27; P=0.002). Doctors were significantly more likely to provide the correct intervention if they worked in a government clinic (OR, 3.03; 95% CI, 1.71–5.35; P<0.001) and had received postgraduate training (OR, 2.26; 95% CI, 1.13–4.52). Finally, screening for type 2 diabetes mellitus was significantly associated with usage of the CPG (OR, 2.41; 95% CI, 1.35–4.29; P=0.003) and working in a government clinic (OR, 1.87; 95% CI, 1.06–3.30; P=0.031).
Discussion
In this study, two of five respondents knew the correct definition of childhood overweight. This is comparable to studies in other countries, where the proportion of doctors who correctly defined the term ranged from 11% to 61%. The reason for the wrong definition was that some doctors were confused by the adult definition of being overweight or used only clinical impressions for diagnosis [7,15-18]. Moreover, similar to reports from other countries, not all doctors measured the BMI of children who visited their clinics [17,19,20]. This study found that the practice of BMI measurement was linked to working in government clinics and using the CPG. This is because the measurement of height, weight, and BMI in children is a routine practice in Malaysian government clinics, as opposed to the individualized practices of private clinics. Improving usage of the CPG may improve the frequency of BMI measurement for patients, thus increasing the likelihood of accurately diagnosing overweight and obesity in children.
Lack of knowledge of the diagnostic criteria and poor BMI measurement practices contribute to the underdiagnosis of childhood obesity, which remains rampant even in other countries [20,21]. Studies in the United States have shown that approximately 4.6% to 24% of children visiting pediatric clinics who fulfilled the obesity criteria were diagnosed with childhood obesity [22-24]. However, attempts by family health practitioners in Canada to improve childhood obesity diagnosis using an electronic health records system integrated with a childhood obesity diagnosis tool have had little success [25].
In addition, four of five doctors provided the correct intervention, which is comparable to that seen in other studies [13,15,18,21]. However, many doctors are still unaware of the correct management or screening methods [7,8,15,20]. This inadequacy translates into inaccurate management when treating overweight children. This was shown in a study conducted in a pediatric primary care clinic in the United States, where only 26% of the children diagnosed with obesity and 20% of children diagnosed as being overweight were given counselling on diet and exercise [24].
Poor diagnosis and management of childhood obesity make children susceptible to long-term complications associated with it, which in turn incur higher medical costs to treat them.
Approximately half the doctors in this study used the CPG. Evidence has revealed that the percentage of doctors who use clinical guidelines for childhood obesity management ranged from 19%–30% [13,17,26]. Despite the CPG being an easily available source of information, not all are fully utilized. This study found that there were higher odds of CPG usage among government clinic doctors, doctors with subspecialty training, and doctors who had worked for less than 5 years. Doctors who worked for less than 5 years could be more motivated to use the CPG as opposed to doctors who had worked for more than 5 years but still had not obtained subspecialty training.
CPG usage was associated with higher odds of screening for, diagnosing, and monitoring complications. This may be because awareness of the guidelines increased adherence to the recommended management [27]. By reading the CPG, the knowledge of primary care doctors is improved, which translates into better identification and management by doctors. The key challenges in achieving this are ensuring that the CPG is kept up-to-date, having good methods of distributing the CPG, and encouraging primary care doctors to read the CPG.
Limitations of the study
One of the major limitations of this study was the low response rate of private doctors. This could have been improved by performing quota sampling among the private doctors via personal visits to various general practitioner clinics to invite them into the study, instead of sending a mass invitation. This led to the study not achieving the required sample size of 313 prior to conducting the study. Despite this, the study found a significant difference in the percentage of doctors using the CPG between government clinics and private clinics.
Answering the survey correctly does not always equate to practicing the correct management methods. An audit of the notes of pediatric patients observed by primary care doctors would offer a more accurate representation of the screening, monitoring, and management practices of the doctors.
Strengths of the study
To the best of our knowledge, this is the first study in Malaysia to assess the understanding of primary care doctors regarding childhood obesity and its association with CPG usage. This shows a significant association between CPG usage and the alleged practices of primary care doctors, which enhances the pool of positive evidence supporting use of the CPG to ratify the weak data available [10-12].
Recommendations
It is recommended that a future study on the actual practices be conducted via audits. Future studies on CPGs could be conducted to prove their effectiveness. Regularly updated CPGs must be drafted and communicated promptly to the intended participants to enhance the knowledge and practices of doctors.
Conclusion
In conclusion, knowledge regarding the diagnosis and management of childhood obesity among primary care doctors is still lacking. CPG on childhood obesity could be a useful tool for improving the diagnosis, management, and screening of childhood obesity.
Notes
Conflict of interest
No potential conflict of interest relevant to this article was reported.
Acknowledgments
The authors would like to thank the Director General of Health, Ministry of Health, Malaysia, for their permission to publish this paper. Special thanks are extended to Dr. Joyce Soo Synn Hong of the University Kebangsaan Malaysia for her invaluable guidance and supervision throughout the study. The authors also wish to thank Associate Professor Dr. Chooi Ling Lim from IMU University for her expertise in statistical analysis and her thoughtful review of this manuscript.
Funding
None.
Data availability
Contact the corresponding author for data availability.
Author contribution
Conceptualization: CWMC, PGL. Data curation: CWMC. Formal analysis: CVMC, KYC. Methodology: CWMC, PGL. Supervision: PGL. Writing–original draft: KYC, CWMC. Writing–review & editing: CWMC, KYC, PGL. Final approval of the manuscript: all authors.
Table 1.
Demographic data of the primary care doctors participating in the online survey
Characteristic
Government doctor (n=128)
Private doctor (n=118)
Sex
Female
109 (85.2)
59 (50.0)
Male
19 (14.8)
59 (50.0)
Working experience (y)
≥10
82 (64.1)
68 (57.6)
<10
46 (35.9)
50 (42.4)
Had postgraduate training
Yes
42 (32.8)
26 (22.0)
No
86 (67.2)
92 (78.0)
Pediatric patients seen per day
<2
11 (8.6)
11 (9.3)
2–10
77 (60.2)
75 (63.6)
>10
40 (31.2)
32 (27.1)
Correct definition of overweight
66 (51.6)
35 (29.7)
Used clinical practice guideline
79 (61.7)
41 (34.7)
Diagnosed pediatric obesity before
114 (89.1)
86 (72.9)
Values are presented as number (%).
Table 2.
Frequency of clinical measurements conducted by primary care doctors
Variable
Never
When clinically indicated
Always
Weight
4 (1.6)
36 (14.6)
206 (83.7)
Height
12 (4.9)
127 (51.6)
107 (43.5)
Body mass index
29 (11.8)
146 (59.3)
71 (28.9)
Waist circumference
87 (35.3)
147 (59.8)
12 (4.9)
Blood pressure
29 (11.8)
136 (55.3)
81 (32.9)
Pubertal status
54 (22.0)
173 (70.3)
19 (7.7)
Values are presented as number (%).
Table 3.
Association between use of CPGs with performing measurements and assessing complications of childhood obesity
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