Study design
This was a post hoc analysis of cross-sectional survey data obtained from a population-level BP screening campaign that was part of the HHA programme. HHA was conducted through a public-private partnership initiative between the Kenya Ministry of Health and AstraZeneca PLC, from February 2015 to October 2018.
Study setting
Details of the HHA programme have been published previously [11]. In summary, the programme was implemented in 17 out of a possible 47 Kenyan counties between March 2015 and March 2016. The main goal of the HHA programme was to reduce barriers to hypertension screening, identification, referral and treatment, through several approaches, including: (1) education and raising awareness of hypertension among healthcare workers (HCWs) and the general public; (2) opt-out facility and community-based screening for hypertension by trained lay providers, especially in non-traditional screening settings such as religious and commercial centres; (3) training of HCWs on the Kenya Ministry of Health-approved hypertension screening and treatment protocol in order to enhance hypertension diagnosis and treatment; and (4) provision of a consistent supply of quality-assured medicines for hypertension treatment.
Standardised registers were used to collect participant information. These data were checked for accuracy, de-identified and uploaded onto a central database monthly.
Participants
The study population was drawn from health facilities and their respective catchment communities. Health facility–based participants comprised adult patients aged 18 years and above who were seeking routine ambulatory health services. Community-based participants were adults aged 18 years and above who volunteered for BP screening at strategically located booths at non-clinical community settings. Trained laypersons conducted the BP screening using standardised protocols [12]. At a minimum, the trained laypersons were high school graduates. Briefly, BP was measured using CE marked Omron M3 digital devises (Omron Healthcare, Kyoto, Japan) with the participant seated in an upright, relaxed position. An appropriate cuff size was selected for each participant, and the cuff was wrapped around the left arm, supported at the level of the heart. Two readings were taken 2 min apart, and the average of the two was recorded. To ensure reliability and validity of the measurements, the lay field assistants received standardised training on BP measurement and the use of standard operating procedures. Trained nurses also carried out regular supportive supervision and provided mentorship and support.
All participants who had a recorded systolic and diastolic BP were included in the analysis. Out of 5,985,185 participants who were screened, 5790 and 6861 had missing systolic and diastolic BP readings, respectively, and were therefore excluded from the analysis.
Data handling
The de-identified analysis database was obtained from the central database in a CSV command delimiter, UTF-16 LE file encoding format. Data were then imported to RStudio using the read.delim function. Data cleaning, decoding, recoding and analysis were performed using RStudio.
Variables
The main outcome variable of interest was prehypertension. This was defined as a systolic BP of 120–139 mmHg and/or diastolic BP of 80–89 mmHg [6]. Other outcomes of interest were normotension and hypertension. Normotension was defined as a systolic BP ≤120 mmHg and a diastolic BP ≤80 mmHg [6]. Hypertension was defined as a systolic BP ≥140 mmHg and/or a diastolic BP ≥90 mmHg [6].
Predictor variables included age (categorized into six age groups: 18–25, 26–35, 36–45, 46–55, 56–65 and 65+ years), sex and place of residence (urban/rural).
A negligible number of participants had missing data for the various variables of interest and were therefore omitted from the final analysis.
Statistical analysis
Descriptive analyses were performed for sociodemographic characteristics of the study population. Categorical variables were presented using proportions. Continuous variables were presented using means with corresponding standard deviations (SDs). Pearson’s chi-square test was used to assess differences in categorical variables. Multivariate logistic regression analysis was performed to identify factors independently associated with prehypertension. Crude and adjusted odds ratios (aORs) are presented. All statistical tests were two-sided, and p values < 0.05 were considered statistically significant. All analyses were performed using RStudio (2015), RStudio: Integrated Development for R (RStudio, Inc., Boston, MA).