The present protocol has been registered within the PROSPERO database (registration ID: CRD42020167175). The present study protocol is being reported in accordance with the reporting guidance provided in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement [34]. (See PRISMA-P checklist in Additional file 1).
Eligibility criteria:
Studies will be selected according to the following criteria: participants, outcome(s) of interest, study design and context.
• Participants (population): We will include studies involving adult cotton textile workers (regardless of gender). We will exclude adults working in another industries (e.g. oil mill, steel mill and coal mill).
• Condition or outcome(s) of interest: The primary outcome will be the prevalence of hypertension (or high blood pressure) indicating the number of people that have the condition divided by the population number at a given point in time. This is often presented as a (prevalence) proportion. We will use author-reported definitions (according to definitions used in the included studies e.g. accepted diagnostic criteria or self-report). Secondary outcomes will be the individual risk factor of hypertension. Potential individual risk factors may include: being overweight or obese, physically inactive, using tobacco, excessive alcohol intake, excessive salt (sodium) in the diet, too little potassium in the diet, stress, or certain chronic conditions (such as kidney disease, diabetes and sleep apnea).
• Study design and context: Eligible studies will be observational studies (cohort, cross-sectional or health surveys) reporting prevalence data using validated or non-validated tools and conducted in low- and middle-income countries. Cross-sectional studies will be the most appropriate study design to determine the prevalence of hypertension. Cross-sectional health surveys are typically used to estimate the point prevalence of common conditions of long duration. For cohort studies, only the first phase (cross-sectional) data will be considered. We will exclude randomized trials, quasi-experimental studies, case studies, case series, qualitative studies, systematic review, protocols, commentaries, and editorials.
• Context/settings: We will include studies conducted in low- and middle-income countries.
No limitations will be imposed on publication status (unpublished studies will be eligible for inclusion e.g. conference proceedings, abstracts). We will only include studies published in English, from January 2000 onwards.
Information sources and search strategy
The primary source of literature will be a structured search of major electronic databases (from January 2000 onwards): MEDLINE (PubMed), CINAHL Plus, Science Direct, and Cochrane Library. The secondary source of potentially relevant material will be a search of the grey or difficult to locate literature, including conference abstracts from selected national or international meeting, thesis dissertations or documents in public repositories. We will perform hand-searching of the reference lists of included studies, relevant reviews, or other relevant documents. The literature searches will be designed and conducted by the review team. The search terms will be grouped into following categories of interest: population (e.g. cotton textile, workers, factory workers, and cotton workers), epidemiological studies (e.g. prevalence, cross-sectional), outcomes (e.g. hypertension, blood pressure, systolic blood pressure, diastolic blood pressure, hypertension, high blood pressure and HTN, risk factors, factors, predictors), and settings (e.g. low- and middle-income countries). Additionally, indexed keywords in the Medical Subject Headings (MeSH) will be used in order to ensure uniform search terms. The search strategy will be piloted to ensure sufficient specificity and sensitivity. A draft search strategy for PubMed/MEDLINE is provided in Additional file 2.
Screening and selection of studies:
All articles identified from the literature search will be uploaded into EndNote [35]. Records will be screened by two reviewers (NA & AF) independently. A pre-defined screening tool will be designed, and a pilot testing will be conducted. First, titles and abstracts of articles returned from initial searches will be screened based on the eligibility criteria outlined above. Second, full texts will be examined in detail and screened for eligibility. Third, references of all considered articles will be hand-searched to identify any relevant report missed in the search strategy. Any disagreements will be resolved by discussion to meet a consensus, if necessary. We will contact the primary author of the study through email in case of any incomplete or missing information. A flow chart showing details of studies included and excluded at each stage of the study selection process will be provided
Data collection process
Data will be extracted onto a customized sheet in Excel that will be pilot tested prior to initiating the data extraction process. This sheet will be completed by two independent reviewers (NA, AF) for the eligible studies. Data extraction tables filled by two reviewers will be compared to confirm that all main findings are included. During the data extraction process a third assessor (SF) will be involved if any discordant data is witnessed. A pilot data extraction table is provided in Additional file 3. Besides, existing studies on this research domain have been revised to assess items in the extraction form. The form included the primary author, year of publication, study setting, country of study, objective, study design, study population, male proportion, average age, BP measurement method, BP measurement apparatus, prevalence of hypertension, average BP risk-factors of hypertension co-morbidities, study limitations, included/excluded, and reason for exclusion, quality appraisal of included studies and reviewer name,.
Evaluation of study quality
The quality of the included studies will be evaluated by standardized quality assessment tool which will be conducted by two authors (NA, AF). Mixed Methods Appraisal Tool (MMAT) tool will be used to evaluate the methodological quality of all non-randomized studies[36]. This tool is used to assess several aspects like selection of study participant, study tool, exposure period, missing data, measurement in outcomes, and selection of the reported result. Two reviewer (NA, AF) will rate each study as critical, serious, moderate, or low risk of bias via judgment of the gathered information. If there is limited information then the risk of bias will be categorized as “no information” or the reviewer will contact corresponding study authors for complete information.
Synthesis of included studies
The data from each paper (e.g. study characteristics, context, participants, outcomes and findings) will be used to build evidence tables of an overall description of included studies. Crude prevalence estimates (number of cases/sample size) will be presented along with 95% confidence intervals. If feasible and appropriate, prevalence data from primary observational studies will be used to perform random effects meta-analyses. Since heterogeneity is expected a priori, we will estimate the pooled prevalence using the random effects model. The random effects model assumes the study prevalence estimates follow a normal distribution, considering both within-study and between-study variation. Forest plots will be used to visualize the extent of heterogeneity among studies. We will quantify statistical heterogeneity by estimating the variance between studies using I2 statistic. The I2 is the proportion of variation in prevalence estimates that is due to genuine variation in prevalence rather than sampling (random) error. I2 ranges between 0% and 100% (with values of 0–25% and 75–100% taken to indicate low and considerable heterogeneity, respectively). We will also report Cochran Q test with a P value of < 0.05 considered statistically significant. If sufficient studies are identified and data points are available, potential sources of heterogeneity will be investigated further by subgroup analyses according to baseline characteristics and methodological covariates. We plan to conduct analyses by gender (male vs. female), age (e.g. young adult, middle-age adult, vs. older adult), years of service, and textile department.
Meta-biases:
If data permits, small study effects (publication bias) will be assessed by inspection of the funnel plots for asymmetry and with Egger’s test and Begg’s test, with the results considered to indicate potential small study effects when P values < 0.10.