Epidemiology of non-communicable diseases among professional drivers in LMICs: a systematic review and meta-analysis

Abstract This systematic review collected evidence on the burden of non-communicable diseases (NCDs) among professional drivers and reported on the most common factors that increase the risk of NCDs in this specific population in low- and middle-income countries (LMICs). The protocol for this systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO). We conducted a thorough search on PubMed/MEDLINE, EMBASE, Scopus, Global Health, Web of Science and Africa-wide information databases on 11 May 2023. We adapted the Joanna Briggs Institute (JBI) tool to assess the quality of the studies. We estimated the prevalence of hypertension, prediabetes, diabetes mellitus (DM), overweight and obesity among professional drivers using a random effect model to compute pooled and subgroup analyses. In addition, we conducted a narrative synthesis of the risk factors and recommendations presented in the included studies. Forty-one studies, including 48 414 study participants, met the criteria for inclusion. The pooled prevalence of hypertension, DM and obesity among professional drivers was 36.7% [95% confidence interval (CI): 31.8–41.6%], 15.2% (95% CI: 7.0–23.4%) and 27.2% (95% CI: 18.7–35.8%), respectively. Unsupportive environment, work stress, sedentary lifestyle, consumption of unhealthy foods and shift work were the most common modifiable risk factors reported. Our findings also show a significant burden of hypertension, DM and obesity among professional drivers in LMICs. The prevalence of DM and obesity was two- and three-fold higher than findings in general populations, respectively. Our findings indicate an urgent need for tailored interventions for different occupation-related risk factors for NCDs among professional drivers in LMICs.


BACKGROUND
A consistent link exists between occupational factors, physical inactivity and non-communicable diseases (NCDs) (Wahid et al., 2016).Compared to the general public, professional drivers are at increased risk of NCDs due to physical inactivity and a sedentary lifestyle from long hours of sitting during distant travels (Udayar et al., 2015), unhealthy diet, obesity (Yosef et al., 2020), harmful alcohol intake and tobacco (Udayar et al., 2015;Rao et al., 2016).Moreover, with work-related stress and tension (Mohsen and Hakim, 2019), changes in the sleep-wake cycle and sleep deprivation further increase their NCD morbidity and mortality risk (Winkleby et al., 1988).
Following increased urbanization and lifestyle changes, there is a transition in the burden of diseases from communicable diseases to NCDs (Bigna and Noubiap, 2019).NCDs are currently the leading cause of mortality, with a total of 41 million deaths each year, accounting for 71% of all deaths globally.Cardiovascular diseases (CVDs), cancers, respiratory diseases and diabetes are the four top killers of NCDs, accounting for 80% of all NCD-related deaths (Forouzanfar et al., 2016).In low-and middle-income countries (LMICs), NCDs are responsible for even more disability-adjusted life years (Arun and Meriton Stanly, 2022).The commonest factors contributing to the rising burden of NCDs are raised blood pressure, tobacco smoking, harmful alcohol consumption, physical inactivity, raised blood glucose and obesity (Holt et al., 2013).Other factors include dietary habits and environmental pollution, as well as the role of genetics (Hamra et al., 2014;Peters et al., 2018).These may act individually or in combination to exacerbate risk.A significant link also exists between occupational factors that are associated with a sedentary lifestyle and physical inactivity and NCDs (Saunders et al., 2020), which may represent key concerns for professional drivers.Research demonstrates that professional drivers across various settings are experiencing an increasing burden of hypertension-and diabetes mellitus (DM)-related deaths (Odeyinka and Ajayi, 2017), which warrants urgent attention.
Occupation and working conditions have a significant role in health promotion and in the development of NCDs, but these have not frequently been addressed in LMICs.As a significant number of individuals spend most of their waking time at work, the workplace serves to influence health risks and outcomes globally (Largo-Wight et al., 2011;International Labour Office, 2012).The increasing burden of NCDs among sedentary workers, including professional drivers, has been reported in a diverse population due to the nature of their work (Rao et al., 2016).
In this paper, professional drivers refer to any individual who drives motor vehicles for a living, including long-haul drivers who are also faced with myriad other factors that predispose them to the double burden of communicable diseases and NCDs.Due to engagement in their work and their working conditions, professional drivers exercise less and have less access to healthcare services.This further increases the gender disparities in healthcare access as males make up the majority of this population (Solomon et al., 2004).In addition to the previously reported high-risk behaviours such as substance use that increased their risk of NCDs, the availability of healthy foods during trips is also a key factor contributing to poor dietary choices and eating behaviours (Bschaden et al., 2019).In India, harmful alcohol use and tobacco smoking were reported in 46% and 35% of drivers, respectively; 42% and 22% were obese and hypertensive, respectively (Girish et al., 2016).
Strategies and interventions for health promotion, prevention and control of NCDs are diverse and require a multisectoral approach beyond the healthcare system (Alwan and MacLean, 2009).With the double burden of diseases in LMICs, the availability and implementation of screening and management services for hypertension, DM and obesity is a challenge, especially among resource-constraint countries (Alwan and MacLean, 2009) where the burden of NCDs is increasing currently, and interventions and occupational health strategies are typically lacking.For example, professional drivers are presented with a unique working environment with minimal workplace health programmes available to address their NCD risk or other health concerns.Moreover, to the best of our knowledge, there is no collated evidence to guide tailored strategies and policies to address the risk of NCDs among professional drivers in LMICs.Such interventions should extend to address the difficulty they face in accessing healthcare services.We aimed to collate evidence on the burden of hypertension, DM and obesity among professional drivers and reported diverse and modifiable factors increasing the risk of NCDs among this sedentary population.

Study design
We developed a systematic review protocol according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) (Moher et al., 2009) before conducting this review.The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database, registration number CRD42022380446.

Eligibility criteria
We included only observational studies (cross-sectional, casecontrol and cohort studies) conducted among professional or commercial drivers diagnosed with the selected NCDs in LMICs.The targeted NCDs include CVDs, hypertension, DM and obesity.We excluded articles not reported in English; systematic reviews and meta-analyses were also excluded at full-text screening; however, we searched the reference list for relevant articles.No publication time limit was applied.

Search strategy
We systematically searched articles from PubMed/MEDLINE, EMBASE, Scopus, Global Health, Web of Science and Africawide information on the 10th and 11th of May 2023.The search included studies conducted in human beings and published in English, with no allocated time limit.We developed a rigorous systematic search strategy with the help of a health sciences librarian with systematic review experience using published guidelines of the Cochrane Collaboration.The strategy was developed for PubMed/MEDLINE using keywords and MeSH terms (MEDLINE) (Supplementary File 1).To be as inclusive as possible, we limited the search strategy to terms covering NCDs and comorbidities among professional drivers and determinants or risk factors for NCDs in LMICs.We used keywords such as NCDs, comorbidities, hypertension, CVDs, diabetes and obesity, prevalence, risk factors, determinants, professional drivers, distant drivers, truck drivers, commercial drivers, LMICs and developing countries.This search strategy was also adapted to the other databases.

Study selection
Study selection was managed using Covidence software (Australia).Two independent reviewers (B.J.N. and H.W.W.) evaluated articles for potential inclusion by screening titles and abstracts and assessed full publications to determine eligibility for final inclusion.Between each assessment, results were discussed to reach a consensus on the interpretation of inclusion criteria.Any further disagreements on study eligibility were resolved by consensus, and a third reviewer (H.P.N.) was consulted when necessary.Duplicate publications were identified and removed using the Covidence software version and manually.The PRISMA flow diagram showing the study selection process and reasons for exclusion is presented in Supplementary Figure 1.

Data extraction
Two reviewers (B.J.N. and H.W.W.) independently extracted data using a standardized data extraction spreadsheet.The data were then compared, and any disagreements were resolved by consensus; the third reviewer (J.M.F.) was consulted when necessary.The data extraction process comprehensively captured information on the author, year of publication, country, study design, data collection period, sample size, response rate, participant and demographic and baseline characteristics, the types of NCDs and reported risk factors.We recorded the number of participants diagnosed with the selected NCDs and the total sampled drivers in the respective studies.Unavailable, unclear information and additional details were requested from the study investigators.Data were recorded in Excel spreadsheet 2020 (Microsoft Corporation, Redmond, WA).

Quality assessment
Two reviewers (H.P.N. and J.M.F.) independently performed and rated the quality of the studies using the respective tools.We used and adapted the Joanna Briggs Institute (JBI) tool for cross-sectional prevalence studies (Munn et al., 2020) to assess the articles as low, moderate and high quality.Disagreement was resolved using arbitration by a third reviewer (B.J.N.).The tool encompassed nine questions with four responses: Yes, No, Unclear or Not applicable.A score of 1 was assigned for 'Yes' responses and 0 for all the other responses.The summary score for each article was obtained by summing the total number of 'Yes' responses.We then categorized the study quality score into low (0-3), medium (4-6) or high (7-9) quality.

Data analysis
We analysed the data using Stata version 17.0.The weighted prevalence [95% confidence interval (CI)] of hypertension, DM, prediabetes, obesity and overweight were estimated using a random effect model and presented in forest plots.We anticipated high heterogeneity across studies due to differences in study populations, design and methods of outcome measurements.We, therefore, computed subgroup analysis by World Health Organization (WHO) regions (Africa, the Americas, the Eastern Mediterranean, Europe, South East Asia and the Western Pacific).We also stratified our findings based on the country's income status, drivers' driving distance and study period.Heterogeneity was assessed using Q and I 2 statistics, where 75%, 50% and 25% indicated high, moderate and low heterogeneity, respectively (Higgins and Li, 2022).Publication bias was evaluated by visually examining the funnel plots of the effect size over standardized error.In addition, Egger's linear regression test of funnel plot asymmetry was also performed (Egger et al., 1997).A p-value of less than 0.05 was considered statistically significant.All analyses were done in STATA 17 (StataCorp, 2023).

Article selection
Our article search obtained a total of 622 publications from six databases.After removing duplicates, 413 were eligible for title and abstract screening.Of 70 articles eligible for full-text screening, 41 met the inclusion criteria and were included in data extraction (Supplementary Figure 1).
The included studies applied different definitions of hypertension; the majority defined hypertension according to the WHO guideline for hypertension management and the local national-level guidelines as a systolic blood pressure of 140 mmHg or diastolic blood pressure of 90 mmHg and above or both (WHO, 2021).Thirteen studies used fasting blood glucose (FBG) for the diagnosis of DM, which is defined as FBG of ≥7.0 mmol/l (≥126 mg/dl), and prediabetes as FBG of 5.6-6.9mmol/l (100-125 mg/dl) (WHO/UCN/NCD/20.1,2020).The remaining 13 studies reported the diagnosis of DM based on random blood glucose (RBG), defined as RBG of >11.1 mmol/l (>200 mg/dl).All except two studies used body mass

Study quality assessment
The quality assessment showed that about half of the studies (52%, n = 21) were of high quality.Seventeen studies (41%) were of moderate quality, and three (7%) were of low quality (Smolarek et al., 2013;Udayar et al., 2015;Appiah et al., 2020).Poor quality recorded for the three studies was mainly due to small sample sizes, unclear outcome assessment methods and the use of non-probabilistic sampling methods (Supplementary Table 1).

Publication bias
We evaluated the possibility of publication bias using visual inspection (funnel plot) and an objective measure (Egger's test).The funnel plot showed an equal distribution of studies from the line of effect.The results from Egger's test showed no significant small study effect bias for hypertension (p = 0.642), diabetes (p = 0.911), prediabetes (p = 0.500), obesity (p = 0.604) and overweight estimates (p = 0.073).

Subgroup analyses of the prevalence of hypertension, DM and obesity by WHO regions, country income status, driving distance and study period
The pooled prevalence of hypertension, DM and obesity was further analysed by the WHO region.The prevalence of hypertension differed by WHO region (p = 0.02); the highest was reported in the Western Pacific (57.0%), followed by Africa (45.2%), and the lowest was in Europe (27.0%).There was no significant difference in the prevalence of DM by WHO regions (p = 0.12); however, the highest prevalence of DM was reported in Southeast Asia (32.3%) (Figure 5).Southeast Asia (38.6%) and Europe (38.4%) had the highest prevalence of obesity, while the West Pacific had the lowest (9.2%) (p < 0.01) (Supplementary Figures 2, 3, 4).
There was no significant difference in the prevalence of hypertension (p = 0.37), DM (p = 0.07) and obesity (p = 0.47) by country income status.Professional drivers engaging in long-distance driving did not have a significantly higher prevalence of hypertension (p = 0.28), DM (p = 0.57) or obesity (p = 0.47) compared to those not engaging in longdistance driving.The highest prevalence of hypertension was reported between 2007 and 2011 (43.0%) and from 2017 to 2021 (42.4%) (p < 0.01).However, the prevalence of DM (p < 0.01) has been significantly increasing (Supplementary Figures 2, 3, 4).

Recommended interventions from the included studies
Different studies reported recommendations for tackling the high burden of NCDs among professional drivers.We summarized the recommendations in four main themes: (i) health promotion through educational programs and public awareness of lifestyle modifications; (ii) regular screening services for NCDs and associated risk factors; (iii) improvement of policies governing the transportation sectors such as driving hours and organization of work and (iv) establishing facilities for physical exercise and recreation (Supplementary Table 3).

DISCUSSION
This review aimed to collate evidence on the burden of hypertension, DM and obesity and reported diverse and modifiable factors increasing the risk of NCDs among professional drivers.Our review reported findings from 41 studies, including 48 414 study participants, that reported the prevalence of the three common NCDs (hypertension, diabetes and obesity) among professional drivers.The pooled prevalence of hypertension, diabetes and obesity was 36.7%, 15.2% and 27.0% respectively.Additionally, 45.1% of all included participants were overweight, and 22.5% had prediabetes.Included studies reported age, overweight, obesity, diabetes, work duration, alcohol use, smoking, high cholesterol levels and family history of CVD as risk factors for hypertension.Participants at risk of DM were older, married, obese, hypertensive and with a positive family history of DM.Physical inactivity and sedentary lifestyle, poor eating practices, using sleep inhibitors and sleeping less than 3 hours were associated with increased odds of obesity.
The hypertension prevalence among professional drivers reported in this study (36.7%) is slightly higher than the overall prevalence of hypertension reported globally (31.1%) in the year 2020 (Mills et al., 2020).Given the projected 30% increase in hypertension prevalence in the general population by the year 2025 (Kearney et al., 2005), our findings imply that the prevalence of hypertension among professional drivers will be approaching an alarming proportion (42%).With a growing body of evidence indicating a higher projected increase in hypertension prevalence in LMICs compared to high-income countries (HICs), it is reasonable to assume that the prevalence gap between professional drivers and the general population will be more pronounced in LMICs.
In 2021, the age-standardized global DM prevalence was 6.1% in the general population; three-quarters of the DM burden was in LMICs (Ong et al., 2023).Similar evidence reported twice the burden in low-income countries compared to HICs (Saeedi et al., 2019).In our context, the overall prevalence of 15.2% among professional drivers in LMICs is more than twice that of the general population.This further substantiates that professional drivers, due to the nature of their occupation that puts them at a higher risk for NCDs, are more affected than the general population (Gona et al., 2021).West Pacific (China) and the Americas regions had the highest DM burden in the current study, similar to the 2021 Global Burden of Disease that showed higher DM prevalence in the Middle East and Latin America regions (Ong et al., 2023).
Sedentary behaviours significantly contribute to overweight and obesity (Silveira et al., 2022).Given that professional driving is a predominantly sedentary job, our study findings further support the association between sedentary occupations and the increased risk of overweight and obesity.In 2019, 8.8% of adult males and 18.5% of adult females were reported to be obese in LMICs (Gona et al., 2021).Our study found that 27.0% of all professional drivers were obese, a prevalence almost 3.07-fold higher than the 8.8% reported among adult males in the general population.
On average, humans spend more than half of their lives engaging in different employment (International Labour Office, 2012).Professional drivers represent a key occupational category that is predominantly sedentary during their working hours.The impact is significantly higher for long-distance driving compared to short distances, with a 4-fold increase in the likelihood of developing NCDs for long-distance drivers (Yosef et al., 2020).Other behavioural patterns that predispose them to NCD risk factors include poor eating behaviours and interrupted sleep patterns with day-night shifts that affect their circadian rhythm (Olson et al., 2017).All of these are known to be the main contributors to NCD in adults (Gómez-Olivé et al., 2018;Twinamasiko et al., 2018).
Additionally, professional drivers are not spared from the other known risk factors for hypertension, diabetes and obesity, such as excessive alcohol consumption and tobacco use, as reported elsewhere (Mills et al., 2020;Ong et al., 2023).Moreover, some of the reported complications of NCDs, such as diabetic retinopathy, neuropathy or medication-induced hypoglycaemia, can impact driving skills and practice (Tamilarasan et al., 2023).Further, there are no established screening interventions for individuals in the driving occupation; it is not only difficult to detect NCDs early for this population, but it is also challenging for the drivers to adhere to treatment under these occupation conditions, leading to adverse health outcomes at the individual level as well as increased risk of road traffic accidents (Almigbal et al., 2018).

Limitations
Our study should be interpreted in the light of the following limitations.A few studies in our analyses were of low quality due to small sample sizes and the use of non-probabilistic sampling methods, which could have decreased the studies' power.The high heterogeneity in our pooled estimates of the included studies was another limitation; this may be due to differences in the study contexts, sampled populations and outcome measurements.On diagnosis-related limitations, most studies did not document three blood pressure readings as recommended hypertension diagnosis, and 50% of studies used RBG alone in documenting DM.Only a few studies reported on the risk factors for NCDs among drivers, so our ability to estimate the pooled risk factors for NCDs among drivers was limited.Other key factors, such as dietary habits and patterns, physical activity, smoking and alcohol intake, were also not documented in the included studies.

CONCLUSION AND RECOMMENDATION
To the best of our knowledge, this is the first systematic review study to report the burden of NCDs among one of the predominantly sedentary occupations, professional drivers, in LMICs.The prevalence of the common NCDs among professional drivers is higher than the reported burden in the general population.The prevalence of DM and obesity were 2-and 3-fold higher compared to findings in general populations, respectively.In addition to the general NCD risk factors, long sitting hours, unhealthy eating behaviours and inconsistent sleep patterns commonly affect professional drivers, predisposing them to a higher likelihood of acquiring NCDs.
Our findings highlight the alarming burden of NCDs on professional drivers whose risks are linked to their occupations.The WHO recommends designing workplaces as healthy settings to promote health and well-being, including prevention, control and interventions for NCDs; this is also highlighted in the WHO Global Action Plan for Worker's Health (Fletcher and Crawford, 2008).This aligns with the global target to reduce physical inactivity in adults and adolescents by 15% by 2023 (WHO, 2018) and the recommended best buys for the prevention and control of NCDs (WHO, 2024).Incorporating NCDs-related interventions at workplaces for professional drivers will provide the most convenient opportunity for detecting and controlling NCDs in this predominantly sedentary population.Such interventions must be tailored to include both preventive and treatment measures for NCDs.We recommend such interventions as useful in combating different occupation-related risk factors for NCDs, such as unsupportive environment, work stress, sedentary lifestyle, consumption of unhealthy foods and shift work (Pg Ismail and Koh, 2014).We recommend interventions such as facilities for physical exercises, psychological support at work, dissemination of educational content on dietary intake and lifestyle, substance use cessation support, education and regulations, and regular NCD screening and referral services at workplaces (International Labour Office, 2012).These health promotion, prevention and intervention strategies for NCDs among professional drivers will require a multisectoral approach beyond the healthcare system (Alwan and MacLean, 2009) and are urgently needed, given the high prevalence reported in this review.

Table 1 :
Characteristics of the included studies