Abstract
Background
Physicians spearhead the prevention and management of cardiovascular diseases, however, there is a paucity of studies that have assessed the cardiovascular risk profiles of physicians in Africa. We aimed to determine the cardiovascular health indices of a cross-section of physicians in Nigeria.
Methodology
A cross-sectional study was conducted among medical doctors in a tertiary hospital in Nigeria, with different specialties being proportionally represented. Sociodemographic, work-associated, and cardiovascular factors, together with anthropometry and Fuster-BEWAT score (FBS): b lood pressure, e xercise, w eight (BMI), a limentation and t obacco were used to assess cardiovascular health indices.
Results
The number of doctors enrolled in this study was 251 with a median age of 34; 51.4 % were males. While the mean FBS was 7.8 (±2.1), 1.6 % of physicians had ideal FBS, as 59.4 % and 39.0 % had intermediate and poor FBS respectively. A small proportion of doctors had adequate fruit or vegetable intake (1.2 %), or exercise (10.4 %). The percentages of doctors who had ideal blood pressure and BMI were 46.6 % and 27.9 % respectively. Almost all doctors were non-smokers (98.4 %). Medical officers and residents had better cardiovascular health compared to consultants. There was no statistically significant association between cardiovascular health score and other work-associated factors.
Conclusion
The composite cardiovascular health index of physicians was assessed as intermediate (7.8 on a maximum scale of 15). Positive metrics were normotensive blood pressure (46.6 %) and tobacco use (98.4 %). We recommend that Nigerian physicians need to improve weight, exercise, and alimentation cardiovascular health practices.
Introduction
Cardiovascular diseases (CVD) are the major cause of death globally, nevertheless, there is clear evidence that this dismal outcome can be ameliorated by early detection and control of its risk factors The sudden onset and spread of Covid-19 infections caused a global snowball of unprecedented healthcare-related stressors with a predicted impact on cardiovascular health. ,
As a result of the impact of Covid-19 on various health systems, the cardiovascular profile of physicians captured the attention of several researchers. This has been studied using different study designs, , individual cardiovascular risk factors, and composite cardiovascular scores. Some investigators have posited that physicians have a continuously stressful work-life and observed that Covid-19 stress factors might have no substantial effect, or exact differing morbidities on different physician cadres. , ,
Medical literature has shown convincingly that the presence of multiple cardiovascular risk factors or clusters in an individual, versus one single risk factor portends greater cardiovascular harm. , This reasoning has produced different composite scores for the study and prediction of cardiovascular disease risk. , The Fuster-BEWAT score (FBS) was recently developed to assess the risk of cardiovascular disease and has been shown to have similar accuracy with the Cardiovascular health score (CVHS), a well-studied and widely used score, in predicting the presence of atherosclerotic plaque and coronary artery calcification. However, the FBS is a simpler and more affordable method
Although several studies have assessed the cardiovascular risk factors of physicians, there is limited knowledge of the cardiovascular profile of Nigerian and African physicians. , ,
This study aims to determine the composite FBS metric of physicians by investigating the individual Fuster-BEWAT factors of b lood pressure, e xercise, w eight (BMI), a limentation, and t obacco, determining the prevalence of ideal, intermediate, and poor FBS status of physicians and their correlation with several work-related, and socio-economic factors.
Methodology
Design
A cross-sectional study was carried out among apparently healthy doctors in a 950-bed tertiary institution in Nigeria during the 3rd wave of the COVID-19 pandemic. The study the study utilized the FUSTER-BEWAT method to assess the participants’ cardiovascular health profiles, and this was analyzed for association for work-related and socio-economic factors.
Inclusion and exclusion criteria
Participants were apparently healthy medical doctors in a tertiary hospital in Lagos, from all the clinical departments and of different cadres. Participants included medical officers (MO), resident doctors, and consultants who consented to be part of the study. Exclusion criteria were medical doctors who were not employed at the hospital like visiting physicians, and those who failed to give consent.
Sample size and sampling method
A minimum recommended sample size of 243 doctors was calculated using the RaoSoft sample size calculator at 95 % power and a prevalence of 50 % for the widest variability, calculated for the sample size A total of 251 medical doctors were recruited out of the 658 doctors working in the hospital at the time. Study participants were selected by proportionate stratified sampling depending on the total number of doctors in each department. Doctors were stratified by their department and then selected proportionate to the number in each clinical department.
Data collection
This study used a blended data collection method, with both a self-administered online, or a physical questionnaire depending on the preference of the participants. Upon receipt of the filled questionnaire, clinical measurements were taken immediately. To minimize the possibility of missing data, there was adequate communication between the investigators and participants. Also, most participants filled out the online questionnaire which could not be submitted if the data was incomplete.
The questionnaire consisted of a consent form and a survey with clinical tools designed specifically for data collection for this study. Data on sociodemographic, Covid-19 risk, and exposure, vaccination status, burnout history (Copenhagen burnout inventory-CBI), personal and family history of CVD, dietary, exercise, and smoking history were collected. Clinical measurements such as weight, height, blood pressure, and waist circumference were taken, and BMI was calculated.
Definition of clinical measurements
The primary outcome of this study was assessing the cardiovascular health score using the FBS and individual cardiovascular factors such as blood pressure, BMI, exercise, dietary intake, and smoking history.
- 1.
Blood pressure: Blood pressure was measured using a digital sphygmomanometer after a 5-minute rest. Two readings were taken 5 minutes apart while the participants were seated; the average was recorded
- 2.
Body Mass Index (BMI): The BMI was calculated by dividing the weight in kilograms by the square of the height in meters (kg/m 2 ). The BMI was divided into 3 categories of underweight (<25 kg/m 2 ), normal weight (25 to 29.9 kg/m 2 ), and overweight/obese (>30.0 kg/m 2 )(23). Weight was measured with a weighing scale in kilograms (kg) with the doctor only putting on light clothing. Height was measured in meters (m) using a stadiometer with the doctor standing upright with feet together and without shoes 3.
- 3.
Waist circumference was measured in centimeters (cm) using a non-stretch linear tape at the widest abdominal circumference. Abdominal obesity was indicated by waist circumference of ≥ 102 cm and ≥88 cm for men and women respectively
All clinical measurements were done by a trained medical doctor.
Fuster-BEWAT score (FBS)
The Fuster-BEWAT score is a non-invasive lifestyle-based cardiovascular health score that includes five components namely blood pressure (B), exercise (E), weight (W), alimentation (A), and tobacco (T). Compared to some other cardiovascular health scores, it is a simplified and cheaper method for assessing cardiovascular risk in low- and middle-income populations. Each component is divided into categories with scores ranging from 0 to 3. A score of 3 is considered ideal while a score of 0, 1, or 2 is not ideal. Respondents were classified as having ideal, intermediate, or poor cardiovascular health according to the total number of ideal components. A score of 4 to 5 was classified as ideal, 2 to 3 as intermediate, and <2 as poor. The total FBS is a summation of the points scored for each parameter. The total score available is 15. . , ,
Data analysis
Data analysis was done using the R statistical software. The categorical and continuous data were summarized as frequencies and means respectively. Association between categorical variables like cadre, frontline worker, work hours/ number of calls, vaccination status, and FBS category were done using a two-tailed Fisher’s exact test while Kruskal Wallis test was used for the continuous dependent variables like blood pressure and BMI; and the Cochran-Mantel-Haenszel test was used to control for possible confounding variables like age, where necessary. A post hoc test to evaluate the direction and size (prevalence ratio) of effect for each level of a given categorical variable was done using Wald’s test (unconditioned maximum likelihood). Due to small numbers, the analysis to test for association between FBS and other variables was done with FBS categorized as good (ideal plus intermediate) and poor. Statistical inferences were made at a significance threshold (p-value) of 0.05, based on the objectives of the study. There was no missing data in this study as the majority of the participants filled out the online questionnaire which permitted submission only when the data needed was complete.
Ethical considerations
Approval of the ethical review board was obtained from the Health Research and Ethics Committee (HREC) of Lagos University Teaching Hospital (LUTH) and the number ADM/DSCST/HREC/APP/4562 was assigned to this study. Verbal informed consent was obtained from each participant.
Results
Descriptive characteristics of participants
A total of 251 medical doctors working at Lagos University Teaching Hospital were enrolled for this study out of 658 doctors. The majority of the respondents were between the ages of 30 to 39 years, with an almost equal proportion of gender (51.4 % were males). Three-fourths of the respondents were resident doctors and 13.5 % were consultants. Thirty-five doctors (13.9 %) had a history of CVD and 182 (72.5 %) reported a family history of CVD. With regards to workload, 32.7 % of the doctors worked for >70 hours per week, and two-fifths of them had 1-2 calls per week with 39 doctors (15.5 %) reporting 5 or more calls in a week. Of the doctors who had 5 or more calls per week, 33.3 % were in surgery and 25.6 % in internal medicine. The proportions of physicians that had personal, work-related, and patient-related burnout were 62.2 %, 52.2 %, and 27.5 % respectively ( Table 1 ).
| Sociodemographic characteristics | Frequency (n = 251) | Percent (%) | |
|---|---|---|---|
| Age(years) | |||
| <30 | 30 | 11.9 | |
| 30-39 | 140 | 55.8 | |
| 40-49 | 66 | 26.3 | |
| ≥50 | 15 | 6.0 | |
| Sex | |||
| Male | 129 | 51.4 | |
| Female | 122 | 48.6 | |
| Cadre in the Medical profession | |||
| Consultant | 34 | 13.5 | |
| Medical Officer | 27 | 10.8 | |
| Resident | 190 | 75.7 | |
| Specialty | |||
| Surgical | 108 | 43.0 | |
| Non-surgical | 108 | 43.0 | |
| Diagnostics | 35 | 13.9 | |
| Years of experience | |||
| 1-5 | 39 | 15.5 | |
| 6-10 | 84 | 33.5 | |
| 11-15 | 81 | 32.3 | |
| 16-20 | 26 | 10.4 | |
| >20 | 21 | 8.4 | |
| Weekly work hours | |||
| 40 | 51 | 20.3 | |
| 41-50 | 42 | 16.7 | |
| 51-60 | 50 | 19.9 | |
| 61-70 | 26 | 10.4 | |
| >70 | 82 | 32.7 | |
| Number of calls per week | |||
| None | 34 | 13.5 | |
| 1-2 | 99 | 39.4 | |
| 3-4 | 79 | 31.5 | |
| ≥5 | 39 | 15.5 | |
| Burnout (CBI) | |||
| Personal | 156 | 62.2 | |
| Work-related | 131 | 52.2 | |
| Patient-related | 69 | 27.5 | |
| Mean total burnout score and SD | 47 ± 18 | ||
Distribution of individual cardiovascular health profile
We found that about half of the doctors had blood pressure (BP) values that were within the normal range (systolic BP <120 and/or diastolic BP <80 mmHg). Only 10 % had BP values within the hypertensive range (SBP >140 and/or DBP >90 mmHg). The mean systolic and diastolic blood pressure were 121 ± 13 mmHg and 75 ± 10 mmHg respectively. The mean BMI and waist circumference were 27 ± 5 kg/m 2 and 92 ± 12 cm respectively. Waist circumference was abnormal in 36.7 % of the doctors. Most doctors (89.6 %) did not meet WHO criteria for the amount of time to be spent on physical exercise in a week. The majority of the respondents were overweight or obese (72.1 %) and consumed <1 serving of fruit/vegetable daily (59.0 %). Only a few (1.6 %) smoked tobacco. Only 13.9 % of the respondents had pre-existing cardiovascular or associated conditions (HTN, DM, PAD, CVD, etc.) and 82.9 % (29 doctors) of that group were compliant with medications or lifestyle modifications. ( Table 2 )
| FBS metrics n = 251 | Cadre | Frontline worker | ||||
|---|---|---|---|---|---|---|
| Consultant n = 34 | Resident n = 190 | MO n = 27 | Yes n = 210 | No n = 41 | ||
| Blood pressure | ||||||
| 0 (SBP >140 and/or DBP >90 mmHg) (n = 25) | 6 (17.6 %) | 17 (8.9 %) | 2 (7.4 %) | 20 (9.5 %) | 5 (12.2 %) | |
| 1 (SBP 130-139 and/or DBP 85-89 mmHg) (n = 27) | 5 (14.7 %) | 21 (11.0 %) | 1 (3.7 %) | 22 (10.5 %) | 5 (12.2 %) | |
| 2 (SBP 120-129 and/or DBP 80-84 mmHg) (n = 82) | 16 (47.1 %) | 57 (30 %) | 9 (33.3 %) | 65 (31.0 %) | 17 (41.5 %) | |
| 3 (SBP <120 and/or DBP <80 mmHg) (n = 117) | 7 (20.5 %) | 95 (50.0 %) | 15 (55.6 %) | 103 (49.0 %) | 14 (34.1 %) | |
| P value | 0.003 (p = 0.068 when controlled for age) | 0.089 | ||||
| Exercise | ||||||
| 0 (<10 minutes of moderate to vigorous exercise/physical activity/week) (n = 117) | 15 (44.1 %) | 92 (48.4 %) | 10 (37.0 %) | 100 (47.6 %) | 17 (41.5 %) | |
| 1 (10-75 minutes of moderate to vigorous exercise/physical activity/week) (n = 72) | 11 (32.4 %) | 53 (27.9 %) | 8 (29.6 %) | 60 (28.6 %) | 12 (29.3 %) | |
| 2 (75-149 minutes of moderate to vigorous exercise/physical activity/week) (n = 36) | 3 (8.8 %) | 30 (15.8 %) | 3 (11.1 %) | 30 (14.3 %) | 6 (14.6 %) | |
| 3 (≥150 minutes of moderate to vigorous exercise/physical activity/week) (n = 26) | 5 (14.7 %) | 15 (7.9 %) | 6 (22.2 %) | 20 (9.5 %) | 6 (14.6 %) | |
| P value | 0.042 | 0.398 | ||||
| Weight (BMI) | ||||||
| 0 (≥30 kg/m 2 ) (n = 59) | 15 (44.1 %) | 38 (20.0 %) | 6 (22.2 %) | 48 (22.9 %) | 11 (26.8 %) | |
| 1 (25 to <30 kg/m 2 ) (n = 122) | 10 (29.4 %) | 98 (51.6 %) | 14 (51.9 %) | 104 (49.5 %) | 18 (43.9 %) | |
| 3 (<25 kg/m 2 ) (n = 70) | 9 (26.5 %) | 54 (28.4.0 %) | 7 (25.9 %) | 58 (27.6 %) | 12 (29.3 %) | |
| P value | 0.047 a | 0.850 | ||||
| Alimentation | ||||||
| 0 (<1 fruit/vegetable serving per day) (n = 148) | 19 (55.9 %) | 112 (58.9 %) | 17 (50.0 %) | 119 (56.7 %) | 29 (70.7 %) | |
| 1 (1-2 fruit/vegetable servings per day) (n = 82) | 10 (29.4 %) | 64 (33.7 %) | 8 (50.0 %) | 74 (35.2 %) | 8 (19.5 %) | |
| 2 (3-4 fruit/vegetable servings per day) (n = 18) | 5 (14.7 %) | 11 (5.8 %) | 2 (0 %) | 16 (7.6 %) | 2 (4.9 %) | |
| 3 (>4 fruit/vegetable servings per day) (n = 3) | 0 (0 %) | 3 (1.6 %) | 0 (0 %) | 1 (0.5 %) | 2 (4.9 %) | |
| P value | 0.661 b | 0.070 | ||||
| Tobacco use | ||||||
| 0 (>1 pack of tobacco per day) (n = 2) | 0 (0 %) | 2 (1.1 %) | 0 (0 %) | 2 (1.0 %) | 0 (0 %) | |
| 1 (<1 pack of tobacco per day) (n = 2) | 0 (0 %) | 2 (1.1 %) | 0 (0 %) | 1 (0.5 %) | 1 (2.4 %) | |
| 3 (Nonsmoker) (n = 247) | 34 (100.0 %) | 186 (97.9 %) | 27 (100.0 %) | 207 (98.6 %) | 40 (97.6 %) | |
| P value | 1 c | 0.512 | ||||
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