Beyond the chalkboard: overnutrition and cardiometabolic health among high school teachers in a semi−urban community in Southwestern Nigeria

Abstract

Background

Cardiometabolic diseases are the leading cause of morbidity and mortality globally. While previous studies have largely focused on in-school adolescents as regards overnutrition and cardiometabolic risk, limited attention has been given to school teachers in Nigeria. This study aimed to determine the prevalence of overnutrition and its association with cardiometabolic risk among high school teachers in Ile-Ife, Southwestern Nigeria.

Method

This was a descriptive cross-sectional study conducted among high school teachers in Ile-Ife, Osun State, Nigeria. Using multistage sampling technique, 252 teachers were recruited from 20 secondary schools. Data were collected using a pre-tested structured questionnaire followed by anthropometric and clinical measurements. According to this study, cardiometabolic risk was operationally defined as presence of at least one of the two parameters: elevated blood pressure (≥ 140/90 mmHg) and elevated blood sugar (≥ 7.8 mmol/L) in each respondent. Data were analyzed with IBM SPSS version 26 with significance set at p < 0.05.

Results

The mean age of participants was 41.9 ± 9.8 years, with 57.9% aged ≥ 40 years. Overall, 54% had overnutrition (30.2% were overweight and 23.8% obese). Elevated blood pressure and elevated blood glucose were found in 17.1% and 5.6% of participants respectively. Cardiometabolic risk was observed in 21% of the teachers. Multivariate logistic regression identified overnutrition (overweight/obesity) as the significant predictor, with overweight teachers being 3.5 times more likely to have cardiometabolic risk (AOR = 3.5, 95% CI:1.47–8.51, p = 0.005) while obese teachers had 7.7 times higher odds of having cardiometabolic risk (AOR = 7.7, 95% CI: 2.83–20.94, p < 0.001) compared to teachers with underweight/normal weight.

Conclusion

This study demonstrated that about 1 in 5 high school teachers had cardiometabolic risk, with overnutrition emerging as the significant predictor. Hence, addressing overnutrition among the school teachers may contribute to improved cardiometabolic health and should be considered in prevention programs.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s40795-026-01428-8.

Background

Cardiometabolic diseases (CMDs) include a group of interconnected disorders including metabolic diseases, such as type 2 diabetes mellitus coupled with cardiovascular diseases (CVDs) such as ischemic heart disease, stroke and heart failure [1–3]. According to the World Health Organization, cardiovascular diseases (CVDs) remain the primary cause of death worldwide, claiming approximately 17.9 million lives annually and significantly truncating global life expectancy [4]. Cardiovascular diseases have emerged as the leading contributors to global morbidity and mortality, often serving as the underlying etiology for sudden cardiac deaths [5, 6]. This escalating burden is intrinsically linked to the global rise in cardiometabolic risk factors such as overweight and obesity driven by rapid nutritional transitions, increased sedentary lifestyles, and physical inactivity [6–8].

Central to understanding the burden of CMDs is the concept of Cardiometabolic risks. Cardiometabolic risk (CMR)is a construct that refers to a clustering of interrelated risk factors that tend to occur together in individuals and are indicative of the cardiometabolic health of individuals [9, 10]. Though CMR classically described within composite diagnostic frameworks such as the International Diabetes Federation (IDF) criteria, CMR consists of modifiable factors that harmoniously potentiates vascular events and metabolic dysfunction and collectively damage cardiac and vascular structures, increasing CVD risk [11]. These risk factors include abdominal (central) obesity, hypertension, hyperglycemia, dyslipidemia, and physical inactivity [5, 10–12]. While these composite frameworks represent the gold standard for metabolic syndrome diagnosis, individual CMR component independently confer significant risk and have demonstrated utility in risk stratification especially in resource constrained settings where biochemical profiling may not be feasible.

A critical component of CMD is hypertension, which affected an estimated 1.4 billion adults aged 30–79 in 2024 [13]. Alarmingly, two-thirds of this population reside in low- and middle-income countries (LMICs), with 44% remaining undiagnosed and unaware of their status [13]. Simultaneously, the global prevalence of obesity has more than doubled over the last three decades [7, 8]. By 2022, 1 in 8 people globally were living with obesity, while 43% of adults were classified as overweight [14]. Although the prevalence of obesity in the African subregion (31%) currently trails the Americas (67%) [15], the trajectory in LMICs is steeply upward due to an increasingly “obesogenic” environment characterized by industrialization and the proliferation of calorie-dense, nutrient-poor diets [14]. In Nigeria, recent systematic reviews estimate the prevalence of overweight and obesity at 25% and 14.3%, respectively, with higher concentrations observed among females and in urban populations [16, 17].

High school teachers represent a demographic particularly susceptible to CMDs due to unique occupational stressors [18–20]. The teaching profession is characterized by stressful working environment in which there are administrative burdens related to school and students management and overseeing large class sizes with growing adolescents [21, 22]. Due to the nature of the profession, teachers are prone to physical inactivity and sedentary behaviours such as prolonged standing or sitting for teaching activities [23, 24]. Despite their pivotal role as health influencers for adolescents, teachers frequently exhibit “at-risk” behaviours, including poor dietary diversity, physical inactivity, and poor sleep [19, 20, 25, 26]. The intersection of occupational stress and poor lifestyle choices among teachers creates a high-risk environment for metabolic failure [19, 27, 28].

Most studies on CMR among school teachers were in developed countries [24, 26, 29, 30], with limited studies done in African settings [20, 23]. While previous studies have largely focused on in-school adolescents as regards overnutrition and cardiometabolic risk in Nigeria [31–34], limited attention has been given to school teachers [18, 35]. Notably, the limited local studies in Nigeria have documented a burden of hypertension and obesity among the school teachers [18, 35]. Overnutrition (overweight/obesity) which is usually assessed through anthropometric measurements has been reported in predicting hypertension and even clustering of cardiometabolic risk factors in previous studies among school teachers [23, 31, 36]. When teachers suffer from chronic CMDs, the educational system is compromised through increased absenteeism, and diminished instructional quality from these teachers which may have far-reaching negative impacts on the educational development of the in-school adolescents and even the economic development of the country [18, 22, 37]. Identifying the burden of overnutrition and cardiometabolic risk in this population is vital for developing targeted workplace wellness programs and policies [18, 19, 29]. This study, therefore, aimed to determine the prevalence of overnutrition and cardiometabolic risk and its association among high school teachers in Ile-Ife, Southwestern Nigeria.

Methodology

Study location and study population

The study was carried out in Ile-Ife, which is an ancient city, a semi-urban community in Osun State, Southwestern Nigeria. The respondents were high school teachers across selected secondary schools in Ile-Ife. Teachers who were pregnant and acutely ill (that could affect their weight) were excluded from the study. Others with disabilities that made them unable to stand were also excluded because of the difficulty it would pose to weighing them.

Sample size and sampling technique

The sample size was determined using single population proportion formula [38], with a prevalence of elevated blood pressure (23.3%) from a previous study [35], a 95% confidence level (Z = 1.96), and a margin of error of 5%. This yielded an initial sample size of 274. Given the finite population of 5,970, the finite population correction (FPC) was applied, calculated minimum sample size was 262. Respondents were recruited from 20 secondary schools in Ile-Ife using two-stage sampling technique. The secondary schools were selected from the two local government areas (LGA) in Ile-Ife. List of secondary schools was obtained from the local inspector of education of each LGA. Firstly, the schools from each LGA were stratified into two, private and public secondary schools. Then, from each stratum, five schools were selected by simple random sampling technique (using computer-based random number generator) per LGA. In total, 10 schools (6 private and 4 public) were selected for each LGA because 60% of the secondary schools were private while 40% were public schools. With the list of the school teachers for each selected school, the respondents were selected using simple random sampling technique (using computer-based random number generator) proportionate to sample size. Of the 262 participants recruited, 252 completed and returned their questionnaires, yielding a response rate of 95.8% and a non-response rate of 4.2%. Although the final sample size of 252 falls marginally below the statistically calculated requirement of 262, it remains sufficient to maintain adequate statistical power for the intended analyses, given that the attrition is minimal and unlikely to compromise the validity of the findings.

Research instruments

A pre-tested, semi-structured questionnaire was used for data collection using the assisted self-administration method. Section A of the questionnaire which covered the sociodemographic characteristics was adapted from the Nigeria Demographic and Health Survey [39]. Section B was developed by the research team to capture the anthropometric and cardiometabolic data of respondents (see supplementary file). Electronic weighing scales were used for measuring weight in kilograms (kg) while stadiometers were used to measure height. Digital sphygmomanometers were used for measuring the blood pressure and glucometers were used for measuring the blood glucose. Pretesting was conducted among twenty-six secondary school teachers in Ile-Ife, who were selected from two schools that were not selected to be part of the study. Areas of ambiguity on the questionnaire were noted and corrected appropriately following the pretesting.

Data collection

Data for this study was collected between July and September 2021. The research team consisted of medical doctors and medical students. Adequate training was conducted by an expert in public health nutrition for the research team on the study instruments and procedures prior to data collection. Data were collected by the research team from the respondents in the morning sessions.

Firstly, the collection of the socio-demographic data of the teachers was done. Then, the measurements (weight, height, blood pressure and random glucose level) from the respondents were conducted. The body weights of the respondents were measured to the nearest 0.1 kg. The teachers removed their footwears and heavy outer garments; they then stood upright with their upper limbs loosely at the sides and their feet flat and together at the center of the weighing scale. Height was measured to the nearest 0.1 centimeters. The teachers stood fully upright without footwear, looking straight ahead, feet flat together at the center of the stadiometer base foot plate, heels against the stadiometer rod, arms hanging loosely at the sides and the stadiometer headboard resting on the head. Height was measured using the stadiometer and weight was measured using the electronic weighing scale. These instruments, stadiometer and electronic weighing scale, had been previously used for studies in similar setting [33, 34]. Blood pressure (systolic and diastolic blood pressure) was measured using the digital sphygmomanometer. Each respondent having sat for at least 5 to 10 min to rest before measurement, blood pressure was measured with the teacher in a sitting position, back supported, feet flat on the floor, clothing sleeve rolled back to leave upper arm uncovered, right arm supported and cubital fossa (inner elbow) approximately at heart level. Two measurements were taken 10 min apart, and the average was taken as blood pressure. This instrument, digital sphygmomanometer, has been previously used for a study in similar setting [34].

Blood sugar levels were measured using the glucometer. For the blood sugar test, single-use disposable non-sterile gloves were used for each participant, as well as a single-use disposable lancet device. The fingertip (left thumb) side of each participant was lanced and the drop of blood obtained was applied to the center of the green field with a beep from glucometer confirming the detection of blood and then the test result was subsequently displayed on the screen. The instrument, glucometer, has been previously used for similar study in this setting [29]. In this study, random blood glucose level was measured due to difficulties in obtaining fasting blood glucose. Previous studies have supported the use random blood glucose in community-based survey for diabetes screening [40–43], and this approach has been previously adopted for a study in similar setting [34].

Measurement of variables

Outcome variable

The outcome variable was cardiometabolic risk. According to this study, cardiometabolic risk was defined as presence of at least one of the two parameters: elevated blood pressure (≥ 140/90 mmHg) and elevated blood sugar (≥ 7.8 mmol/L), in each respondent. This aligned with studies conducted on clustering of cardiometabolic risks that assessed more than one cardiometabolic risk factor [19, 22, 44, 45].

Explanatory variables

The explanatory variables utilized in the study were based on literature review of existing studies [23, 29, 35]. The body mass index (BMI) was computed from the variables of weight and height and later classified according to WHO standard [46]. The main explanatory variable was overnutrition which was regarded as being overweight (BMI: 25.0–29.9 kg/m²) and obesity (BMI: ≥ 30.0 kg/m²) [46].

Covariates included the sociodemographic characteristics which were age (< 40 and ≥ 40), sex (male and female), income (≤ 70,000 and > 70,000), teaching experience (< 10, 10–19 and ≥ 20), marital status (single and ever married), ethnicity (Yoruba, Hausa, Igbo and others) and religion (Christianity, Islam and Traditional). Age was classified into 2 categories (< 40 and ≥ 40) based on previous studies on adults including a systematic review on school teachers which consistently identified increasing age, particularly beyond 40 years, as an important risk factor for cardiometabolic risk [17, 47, 48]. Income was classified into the two groups on the basis of the minimum monthly salary by law for any Nigerian worker [49]. For inferential statistics, variables such as BMI and ethnicity were reclassified due to small data in subcategories. BMI was reclassified into three categories, underweight/normal, overweight and obesity, because 6.3% of the respondents were underweight. Ethnicity was reclassified into two categories, Yoruba and others, because 0%, 2% and 2.8% of the respondents were Hausa, Igbo and others respectively.

Data analysis

All administered questionnaires were collected and checked daily for completeness and errors before entry into a computer. The obtained data was analyzed using IBM SPSS version 26. Descriptive analysis of all the variables measured was firstly done. The categorical variables were summarized and reported as frequencies and proportions, while the continuous variables were summarized and reported as mean and standard deviation for data which was normally distributed. For bivariate analysis, Pearson chi-square test was used to determine association between the explanatory variables and the outcome variable (cardiometabolic risk). Variables significant at bivariate analysis (p < 0.05), together with theoretically important confounders identified a priori from the literature, were entered into the multivariable binary logistic regression model to identify the independent predictors of cardiometabolic risk. For all statistical tests in this, the level of significance was set at p < 0.05 at a 95% confidence interval.

Results

A total of 252 respondents comprising of 65.5% female (n = 165) and 34.5% male (n = 87) were analysed. The mean age of respondents was 41.9 ± 9.7 years, with the majority (57.9%) aged ≥ 40 years. Overall, 17.1% (n = 43) of the respondents had elevated blood pressure, while 82.9% (n = 209) had normal blood pressure. For blood glucose, 5.6% (n = 14) had elevated random blood sugar, whereas 94.4% (n = 238) had normal levels. The prevalence of cardiometabolic risk (defined as elevated blood pressure and/or elevated blood sugar) was 20.6% among the study population (Fig. 1). In terms of BMI classification, 30.2% (n = 76) were overweight and 23.8% (n = 60) were obese, while 39.7% (n = 100) had normal BMI and 6.3% (n = 16) were underweight. This indicates that more than half of the teachers (54%) were experiencing overnutrition. (Table 1)

Fig. 1.

Prevalence of cardiometabolic risk among high school teachers in Ile-Ife, Nigeria

Table 1.

Descriptive analysis of cardiometabolic risk factors and the explanatory variables (N = 252)

Variables	Frequency (%)
Cardiometabolic risk factors
Blood pressure (mmHg)
Normal	209 (82.9)
Elevated	43 (17.1)
Random blood sugar (mg/dl)
Normal	238 (94.4)
Elevated	14 (5.6)
Explanatory variables
Body mass index (kg/m2)
Underweight	16 (6.3)
Normal	100 (39.7)
Overweight	76 (30.2)
Obesity	60 (23.8)
Age (years)
< 40	106 (42.1)
≥40	146 (57.9)
Mean age ± SD	41.9 ± 9.7
Sex
Male	87 (34.5)
Female	165 (65.5)
Religion
Christianity	204 (81.0)
Islam	48 (19.0)
Traditional	0 (0)
Ethnicity
Yoruba	240 (95.2)
Hausa	0 (0)
Igbo	5 (2.0)
Others	7 (2.8)
Years of teaching experience
< 10	90 (35.7)
10–19	95 (37.7)
≥ 20	67 (26.6)
Mean ± SD	13.9 ± 9.1
Level of education
Secondary	5 (2.0)
NCE/OND	50 (19.8)
HND/BSC	142 (56.3)
Post-Graduate	55 (21.8)
Marital status
Single	36 (14.3)
Ever married	216 (85.7)
Family setting
Monogamous	216 (85.7)
Polygamous	36 (14.3)
Income (Naira)
≤ 70,000	204 (81.0)
> 70,000	48 (19.0)
Mean ± SD	50,000 ± 30,000

SD standard deviation, NCE National Certificate of Education, OND Ordinary National Diploma, HND Higher National Diploma, BSC Bachelor of Science

Cardiometabolic risk varied significantly across the explanatory variables as shown by Table 2. The teachers’ body mass index (BMI) was significantly associated with cardiometabolic risk. Only about one in ten respondents with underweight or normal BMI (9.5%) had cardiometabolic risk, whereas more than a quarter of those who were overweight (26.3%) and over a third of those who were obese (38.3%) were affected. Age of the respondents also showed a significant association with cardiometabolic risk such that teachers who were above 40 years had more than twice the prevalence of cardiometabolic risk (29.2%) compared to those aged 40 years or younger (13.1%). The number of years of teaching experience was significantly related to cardiometabolic risk. Those with 20 years or more of teaching experience had the highest prevalence (34.3%), compared to 16.9% among those with less than 10 years and 16.8% among those with 10 − 19 years of experience. Income was also significantly associated with cardiometabolic risk. Teachers earning more than 70,000 Naira monthly had a markedly higher prevalence of cardiometabolic risk (37.5%) compared to those earning 70,000 Naira or less (17.6%).

Table 2.

Association between explanatory variables and cardiometabolic risk

Variables	Cardiometabolic risk		Statistic
	Absent	Present
BMI
Underweight/Normal	105 (90.5)	11 (9.5)	χ2  = 21.64
Overweight	56 (73.7)	20 (26.3)	p < 0.001*
Obesity	37 (61.7)	23 (38.3)
Age (years)
≤ 40	106 (86.9)	16 (13.1)	χ2  = 9.71
> 40	92 (70.8)	38 (29.2)	p = 0.002*
Sex
Male	69 (79.3)	18 (20.7)	χ2  = 0.043
Female	129 (78.2)	36 (21.8)	p = 0.836
Years of teaching
< 10	74 (83.1)	15 (16.9)	χ2  = 8.89
10–19	79 (83.2)	16 (16.8)	p= 0.012*
≥ 20	44 (65.7)	23 (34.3)
Income (Naira)
≤ 70,000	168 (82.4)	36 (17.6)	χ2  = 9.09
> 70,000	30 (62.5)	18 (37.5)	p = 0.003
Marital status
Single	32 (88.9)	4 (11.1)	χ2  = 2.66
Ever married	166 (76.9)	50 (23.1)	p = 0.103
Ethnicity
Yoruba	188 (78.3)	52 (21.7)	χ2  = 0.170
Others	10 (83.3)	2 (16.7)	ap = 1.000
Level of education
Secondary	4 (80.0)	1 (20.0)	χ2  = 1.19
NCE/OND	38 (76.0)	12 (24.0)	p = 0.755
HND/BSC	110 (77.5)	32 (22.5)
Post-graduate	46 (83.6)	9 (16.4)
Family setting
Monogamous	168 (77.8)	48 (22.2)	χ2  = 0.57
Polygamous	30 (83.3)	6 (16.7)	p = 0.452

*Statistically significant, χ² = Chi square, p = p-value, ^aFisher’s exact test

Other sociodemographic variables, including sex, marital status, ethnicity, level of education, and family setting, did not show statistically significant associations with cardiometabolic risk.

The factors associated with cardiometabolic risk among secondary school teachers in Ile-Ife was shown in Table 3. Teachers who were overweight had more than three times the odds of cardiometabolic risk compared to those with normal or underweight BMI (AOR = 3.5, 95% CI: 1.47–8.51), while those who were obese had nearly eight times the odds (AOR = 7.7, 95% CI: 2.83–20.94). Although age was significantly associated with cardiometabolic risk in the unadjusted model (COR = 2.7, p = 0.002), this relationship lost statistical significance after adjustment (AOR = 1.8, p = 0.233). Similarly, income and years of teaching experience showed significant associations in the crude analysis but were attenuated in the adjusted model. Teachers earning above 70,000 Naira monthly and those with ≥ 20 years of teaching experience initially appeared more likely to have cardiometabolic risk, but these associations were not sustained after controlling for other factors.

Table 3.

Factors associated with cardiometabolic risk among the school teachers

Variables		Unadjusted model		Adjusted model
		COR (95% C.I)	p-value	AOR (95% C.I)	p-value
BMI	Underweight/Normal
	Overweight	3.4 (1.53–7.62)	0.003	3.5 (1.47–8.51)	0.005*
	Obesity	5.9 (2.64–13.34)	< 0.001	7.7 (2.83–20.94)	< 0.001*
Age (years)	< 40
	≥ 40	2.7 (1.43–5.23)	0.002	1.8 (0.69–4.45)	0.233
Sex	Male
	Female	1.1 (0.57–2.02)	0.836	0.5 (0.22–1.09)	0.079
Income (Naira)	≤ 70,000
	> 70,000	2.8 (1.41–5.56)	0.003	1.8 (0.74–4.42)	0.197
Years of teaching	< 10
	10–19	1.0 (0.46– 2.16)	1.0	0.5 (0.19–1.29)	0.153
	≥ 20	2.6 (1.22–5.46)	0.013	0.7 (0.22–2.31)	0.578
Marital status	Single
	Ever married	2.4 (0.81–7.14)	0.113	1.6 (0.49–5.39)	0.423

COR crude odds ratio, AOR adjusted odds ratio, CI confidence interval

*Statistically significant

Discussion

Cardiometabolic diseases remain the leading global burden for morbidity and mortality worldwide, affecting varied population across all ages and both sexes [11]. This study aimed to determine the prevalence of overnutrition and cardiometabolic risk and its association among high school teachers in Ile-Ife, Southwestern Nigeria. It differed from other studies in that it focused on cardiometabolic risk assessment among teaching professionals who are crucial to the development of in-school adolescents [27].

The prevalence of overnutrition from current study was 54%, with overweight and obesity being 30.2% and 23.8% respectively. This suggests that 1 out of 2 school teachers had overnutrition. Compared with the prevalence of overnutrition that ranged from 57% to 60% in studies done in Southwestern Nigeria in 2017 [18], Eastern Nigeria (Abia State) in 2022 [35], and Eastern Nigeria (Calabar) in 2024 [27] among school teachers, this current study revealed a slightly lower prevalence of overnutrition (54%). While the prevalence of overnutrition from current study was lower than the reported overnutrition prevalence among school teachers of 64.5% in Indonesia in 2019 [29], and 64.5% in Saudi-Arabia in 2023 [50], overnutrition was observed higher in our study than the recorded prevalence of 43.7% from the study done in Benin in 2024 [51]. The variation could be as a result of differences in study location as the previous studies were done in urban settings in Asia continent compared to our study done in a semi-urban community in Africa. The difference in settings may partly reflect differences in dietary patterns, socioeconomic characteristics, food choices or lifestyle behaviours, possibly leading to the variation in overnutrition among school teachers in different countries. The high prevalence of overnutrition found among teachers may be partly explained by the sedentary nature of teaching [47, 52]. Evidence from systematic reviews about workforce in Nigeria [52], Europe [53] and some studies in other settings indicate that teachers often exhibit low levels of physical activity and prolonged sedentary behaviour while teaching students [22, 24, 29]. The high prevalence of overnutrition among the school teachers should be a concern for the policy makers and stakeholders and governing institutions of schools.

We observed the prevalence of elevated blood pressure among the school teachers was 17.1%. This indicates that about 1 out of 5 school teachers had elevated blood pressure (EBP). Compared with the prevalence of EBP ranging from 24% to 29% in studies done in Southwestern Nigeria in 2017 [18], Eastern Nigeria (Abia State) in 2022 [35], and Eastern Nigeria (Calabar) in 2024 [27] among school teachers, this current study revealed a lower prevalence of EBP (17.1%). While the prevalence of EBP from current study was lower than that from studies done among school teachers in Indonesia in 2019 and Egypt in 2024 [23, 29], the prevalence of EBP was observed higher than the findings from studies done in Saudi Arabia in 2023 and Benin in 2024 [50, 51]. These studies highlight differences in the prevalence of EBP among school teachers from different regions. These variations may be due to differences in study methods and periods or to some socio-cultural and economic factors.

From our study, the prevalence of elevated blood glucose (EBG) was 5.6%. Compared with findings from studies done in Indonesia in 2019 [29], in Saudi Arabia in 2023 [50], and in Egypt in 2024 [23] among school teachers, this current study revealed lower prevalence of elevated blood glucose. This variation may be related to difference in the measurement method of blood glucose level among the respondents. Random blood glucose (RBG) was measured in our study which was different from fasting blood glucose (FBG) measured in the previous studies. In our study, RBG level was measured due to difficulties in obtaining teachers’ compliance with overnight fasting. Notably, studies have supported the use of RBG in community-based survey for diabetes screening [40–43], and this approach has been previously adopted for a study in similar setting [34]. The low prevalence of EBG reported in this study is similar to observations from studies assessing blood glucose level among Nigerian adults [41, 54, 55]. A slower or more prolonged pathophysiology of glucose intolerance may be the result for the low prevalence of EBG [34].

From our study, the prevalence of cardiometabolic risk (clustering of one or two cardiometabolic abnormalities: elevated blood pressure or blood glucose) was 21%. Clustering of 1 or more cardiometabolic risk factors have been reported, from previous studies, to increase the risk of cardiovascular disease morbidity and mortality [22, 44, 45], with suggestions that the magnitude of CVD relating to these risk factors is rising as the prevalence of the risk factors increases [55, 56]. To the best of our knowledge, after a diligent literature search, we could not find a study in Nigeria done among school teachers relating to clustering of one or two cardiometabolic abnormalities. Therefore, no comparisons could be made within Nigeria. Meanwhile, compared with findings from studies on cardiometabolic risk done among school teachers in India where reported prevalence ranged from 38% to 48% [19, 22], our study revealed lower prevalence of cardiometabolic risk. The variation could be as a result of difference in clustering of the cardiometabolic risk factors. In the previous studies, the two cardiometabolic risk factors clustered were not clearly defined, and so may be different from the factors clustered in our study [19, 22]. The clustering of elevated blood pressure and elevated blood glucose in our study may reflect the possible co-occurrence of hypertension and diabetes mellitus which have been commonly reported among adult population in African and Nigerian settings [57–59].

Another finding in this study was the significant association between overnutrition and cardiometabolic risk. Teachers with overnutrition (overweight and obesity) were far more likely to have cardiometabolic risk compared with teachers with normal or underweight. This finding was consistent with evidence from previous studies [23, 29]. Notably, we observed in our study that the obese school teachers had seven times higher odds of cardiometabolic risk compared to overweight teachers who had three times higher odds of cardiometabolic risk than normal/underweight teachers, meaning the higher the BMI the greater the cardiometabolic risk. This is in keeping with previous studies which have shown that obesity is associated with higher odds of cardiometabolic risk than overweight [33, 60]. The observed wide confidence interval for the association between obesity and cardiometabolic risk in this study was similarly noted in previous studies done among school population in Nigeria involving sample size ranging from 455 to 1000 [33, 61]. However, this observation was different from that found in a meta-analysis study done with sample size of more than 120,000 from USA and Europe [60]. Difference in study population and small subgroup size may partly explain the variation with the confidence interval even though there was significant association between obesity and cardiometabolic risk in those studies.

The mechanism linking obesity to cardiometabolic risk (presence of elevated blood pressure or elevated blood glucose) has been mentioned in the literature [62, 63]. Excess adipose tissue releases free fatty acids and pro-inflammatory cytokines, which impair endothelial function and insulin sensitivity [62]. These changes foster vascular remodeling, elevate blood pressure, and increase diabetes risk [63, 64]. Obesity coupled with uncontrolled condition of elevated blood pressure or elevated blood glucose may cause impairment and disability among the school teachers [12]. This may lead to reduced work capacity, work productivity and may eventually contribute to increased absenteeism of the teachers from the school [27, 37]. Essentially, our observation from this study findings point at a critical concern to be addressed by relevant stakeholders and policy makers and corroborate the need for monitoring of the nutritional status by simple regular screenings using weighing scale and tape measures in school, as well as screening for other cardiometabolic risks even among the school teachers [21, 22, 27].

Strengths and limitations of the study

The strength of this study lies in integrating anthropometric, blood pressure and blood glucose measurements rather than focusing on a single variable in assessing the cardiometabolic risk of the teachers. This provides a more robust insight into cardiometabolic health among teachers than the previous studies in Nigeria.

However, certain limitations must be acknowledged. As this was a cross-sectional study, causal relationships could not be established. Also, the possibility of recall and social desirability bias could not be entirely excluded because the sociodemographic data was self-reported. The study was conducted in a semi-urban setting, which may limit generalizability to rural or urban populations. Random blood glucose (RBG) was measured instead of fasting blood glucose which limited our comparison with previous studies on metabolic syndrome among school teachers although RBG has been supported to be useful in diabetes screening in community-based survey. Dyslipidemia was not assessed among our respondents which also limited us assessing metabolic syndrome and comparing with other studies on metabolic syndrome among the school teachers. Elevated blood pressure was used in this study and not hypertension because the requirement of two or more readings on separate occasions for the diagnosis of hypertension could not be met in this community-based survey. However, given the cross-sectional study design for this study, this approach was appropriate. We adjusted our analyses for age, sex and income, years of teaching; however, there are additional confounders which we did not measure and are unable to consider (e.g., dietary intake, physical activity and occupational stress).

Recommendations

Ministries of health and education should collaborate to design workplace wellness programs that promote healthier diets and regular physical activity for school teachers. Routine screening programs such as nutritional and blood pressure screening should be provided for school teachers. Identifying cardiometabolic risk among school teachers may promote their health status and improve their work productivity [18, 27].

Conclusion

This study demonstrated prevalence of cardiometabolic risk among high school teachers in Ile-Ife with overnutrition emerging as the significant predictor. Teachers who were overweight or obese were more likely to have cardiometabolic risk compared to those with normal BMI. Addressing overnutrition among the school teachers may contribute to improved cardiometabolic health and should be considered in prevention programs.

Abbreviations

BMI

Body Mass index

BP

Blood Pressure

CMR

Cardiometabolic risk

CI

Confidence Interval

DPB

Diastolic Blood Pressure

EBG

Elevated Blood Glucose

EBP

Elevated Blood Pressure

LMIC

Low- and middle-income countries

OR

Odds Ratio

RBS

Random Blood Sugar

SBP

Systolic Blood Pressure

WHO

World Health Organization

Authors’ contributions

The topic was conceptualized by OOO, CAO, ETA and AAA Background was written by CAO and ETA while methodology and results were by OOO Data collection and initial analysis were done by FR, OO, OA, OS. Further data analysis was done by OOO, AAA. Discussion was written by ETA, CAO and OOO All authors read and approved the final version of the manuscript.

Funding

No funding was received for this study. It was fully funded by the authors.

Data availability

Dataset will be made available on reasonable request.

Declarations

Ethics approval and consent to participate

Ethical approval for this study was granted by the Health Research Ethics Committee of the Institute of Public Health, Obafemi Awolowo University, Ile-Ife (HREC Number: IPH/OAU/12/1607). Permission was obtained from the heads of the selected schools. Informed consent was obtained from the teachers. In accordance with the Nuremberg code and the Declaration of Helsinki, the principles of informed consent, respect for participants, fair subject selection and favourable risk benefit ratio were followed. Important information on the participants’ information sheet included that the information volunteered will be kept confidential as all questionnaires were coded without names or addresses of respondents. It also emphasized that participants were free to opt-out if they were not comfortable with the information in the questionnaire. Signed consent forms were then obtained from the respondents.

Consent for publication

Not applicable. However, all authors gave consent for publication of this manuscript.

Competing interests

The authors declare no competing interests.