Hypertension and diabetes in Africa: design and implementation of a large population-based study of burden and risk factors in rural and urban Malawi

The study is part of a collaborative research programme by the Malawi Epidemiology and Intervention Research Unit (MEIRU), previously Karonga Prevention Study (KPS); a partnership between the London School of Hygiene and Tropical Medicine, the Malawi Ministry of Health (MoH) and the Malawi College of Medicine, funded through a Strategic Award from the Wellcome Trust. The key research questions were developed jointly in a stakeholders’ meeting in Lilongwe, the capital city of Malawi, attended by policy makers, policy implementers and researchers; the ideas were discussed in the context of the Malawi National Health Research Agenda [20]. The NCD research was developed as extension of a long-standing programme of medical research (focussing on Leprosy, TB and HIV) in the rural site in Karonga. The partners were consulted on selection of a new urban study site in Lilongwe, which was established to enable rural–urban comparison of findings.

The high level objectives of the work, laid out in the funding proposals, were to undertake internationally leading research on the control of important non-communicable diseases relevant to Africa in partnership with the College of Medicine and the Ministry of Health, Malawi, and to develop research capacity.

More specifically we proposed to quantify the burden of specific NCDs, their risk factors and the barriers to accessing care, and to design and evaluate interventions which lead to effective NCD control in Africa by; (1) determining the burden of the major NCD risk factors—hypertension, diabetes, hyperlipidaemia, smoking, obesity, physical inactivity and alcohol, salt and saturated fat intake—and exploring how these vary between urban and rural populations, with age and gender; (2) describing the uptake of and retention in care among patients identified during screening with hypertension or diabetes and referred to clinical services; and (3) measuring the prevalence and clustering of NCD risk factors in people with HIV/AIDS (on ART or not on ART).

In the rural DSS, all 18,000 adults will be invited to participate. It is anticipated that by the conclusion of enumeration of the urban study site that 23,000 adults will be identified and invited. The large sample size will enable (a) calculation of precise age-sex urban/rural specific prevalence of key outcomes and risk factors and their distribution and clustering by HIV and socio-economic status; (b) examination of associations between outcomes and risk factors, for example characterising the relationships between anthropometric indices and outcomes in different age- and sex- groups and exploring urban rural differences in these relationships; (c) generation of baseline data on cohorts of a adequate size for future estimates of incidence of diabetes and hypertension; and (d) creation of cohorts of newly diagnosed diabetic and hypertensive patients and people with impaired fasting glucose or early hypertension. This will facilitate detailed future studies to investigate the natural course of disease and/or impacts of potential interventions.

As with most African countries, Malawi is undergoing urbanisation, but currently more than 80 % of the population live in the rural areas [21]. A rural and an urban area were included to explore the differences in lifestyle and prevalence of outcomes associated with urbanisation—the Demographic Surveillance Site (DSS) in southern Karonga (Northern Region, Malawi) as a typical rural population, and Area 25 of Lilongwe City (Central Region, Region) representing urban populations. The rural area is an established research site [22] and the urban site was considered appropriate for conducting the NCD studies, as the resident population represents a broad spectrum of socio-economic groups and the MoH planned to establish a chronic care clinic at the Area 25 health centre.

In Karonga, the study was nested in the Karonga DSS which was set up in August 2002 with a baseline census to register all individuals and households in the study area [23]. Reporting by village informants on vital events and migrations forms a continuous registration system. The DSS is located on latitude −10.43° and longitude 34.27° and is bordered by Lake Malawi in the east, Nyika National Park in the west; the north and south demarcation follows village boundaries (Fig. 1). The DSS has a population of about 36,000 individuals based on 2012 mid-year population estimates, most of whom are rural dwellers who depend on subsistence farming and fishing for their livelihoods [24] and are scattered over an area of 135 km². There are two small trading centres and a port and truck depot. The DSS area is served by two hospitals: Karonga District Hospital which is 70 km from the DSS; and Chilumba Rural Hospital which along with four minor health centres, is within the surveillance site.

Lilongwe, declared the capital city of Malawi in 1975, is one of four cities in Malawi. Area 25 is a residential area located on latitude −13.95° and longitude 33.76° (Fig. 1). The area is a mixed urban population with civil servants, commercial and non-governmental organisation employees as well as students and large populations in casual and informal employment or petty trading, and seeking work. Much of the commercial employment is with tobacco processing factories and industrial estates that are located approximately 5 km from the study area. Area 25 is considered a traditional high density area, it covers land area of about 23 km² hectares and reached a population of 64,650 in 2008 which rose from 39,132 in 2005 [25]. Area 25 is served by one primary government health centre and one mission health centre located within the study area and is approximately 15 km from Kamuzu Central Hospital, the main tertiary hospital in Lilongwe, and 20 km from Bwaila Hospital, which functions as a secondary referral centre.

Although the prevalence of diabetes and hypertension are low in younger people (<25 years), all adults aged 18 years and above were invited to take part in the study, in contrast to most studies which have excluded individuals of less than 25 years old, because of expected low outcome rates. The rational for including this age group was to enable future investigations into associations between exposures experienced in younger adult life and risk for development of NCDs in later life, and for comparing trends over time in different age cohorts. An upper age restriction was not imposed, so that the total burden of diseases in this population could be described, including the urban/rural differences that might be driven by the contrasting age distributions.

All adults normally resident at a household (i.e. not a temporary member with intent to leave) in either of the study areas and able to consent were eligible to be included in the study, from May 2013 onwards. Individuals who identified themselves as visitors were excluded.

In the Karonga DSS each village is divided for vital events reporting purposes into smaller geographical area (“clusters”) that represent an average of 35 households (Fig. 2). Groups of approximately 10 clusters in a defined geographical area are combined to form the 21 reporting groups (henceforth “study zones”), which make up the surveillance area. Detailed methods of the demographic surveillance are described elsewhere [24].

In Lilongwe, Area 25 can be sub-divided into 35 Enumeration areas (Fig. 3), demarcated by the National Statistical Office during the 2008 population and household census, which have, on average 480 households each. These were used as administrative boundaries of “study zones” for the survey.

Sensitization took place at district and community levels: initially with the District Health Offices and in the urban area, the police and the city council, later with traditional authorities and local head(wo)men. In both rural and urban areas periodic meetings were held, attracting between 150 and 800 people, where drama and song were used as communication tools. In the urban area a vehicle-mounted public address system was used to further inform the public prior to enumeration. Leaflets and information sheets about the study were distributed prior to the survey, introducing the partners engaged in the study and the funding body, and including information on what the participants should expect if they take part in the study. This included the meaning of “participation”, rationale for blood sampling and destination of the samples, and the risk and benefits of taking part.

In Lilongwe as a new site, enumeration was conducted prior to the conduct of the survey. This process involved systematically approaching each household and identifying a suitable informant, (a resident, a domestic worker or in some cases a neighbour), to collect the required data on household membership; names and sex of household members thought to be close to 18 years old or above, and location details. Global positioning system (GPS) co-ordinates were collected using the tablet computer and every household was given a unique “household” number which is bar-coded, scanned onto the household electronic data collection form, and chalked onto a door or gate post. These enumeration data were printed out to create a hard copy register for each sector listing households, GPS co-ordinates and the name and sex of members presumed to be eligible. After the first 7 months of field work, there was a lapse between enumeration and survey, permanently resident households and individuals new to the area who had not been enumerated were added to the registers at the time of the survey.

In the rural area, a hard copy register was printed for each cluster as required, with the same information (with the addition of age), generated from up-to-date demographic surveillance data, to facilitate the field work there. Details of the DSS procedures are described elsewhere [22], but it is important to note that births and deaths are reported on a monthly basis and migrations updated annually.

The field and clinical teams recruited for the survey underwent a 15 day training programme on use of electronic data capture devices, collection of biophysical measurements, hypertension and diabetes, lifestyle counselling, blood samples collection and handling, full (or refresher) HIV counselling training and research ethics as appropriate. Consent, questionnaire and measurement procedures were tested and piloted repeatedly in workshops at both sites, initially on team members, then colleagues, then on volunteer members of the public. Pilots included blood draws and laboratory analysis. Project and government clinical and nursing staff underwent training on lifestyle counselling and management of diabetes and hypertension.

The study protocol was developed through collaboration between scientists from the urban and rural site, and cross-site team visits, for all cadres of staff, were conducted for training and implementation of field work. The study was managed by a senior team who had oversight of both rural and urban sites.

Development of the study questionnaire was heavily informed by existing questionnaires including the WHO Physical activity questionnaire [26] Hyderabad [27, 28] Blantyre Health Study [29] and the STEPS survey questionnaire [13], to enable comparison with findings in other settings, as well as standard questionnaires from previous KPS studies. Anthropometric and blood pressure measurements were done to standardised protocols.

Five teams of fieldworkers (each consisting of nurse, male interviewer and female interviewer) were deployed in each site, supported by a field supervisor. The field work was managed in such a way that female field interviewers could examine female study participants and male field interviewers are could examine male study participants when requested—particularly when taking waist and hip measurements.

Android operating system tablets were used for main survey data collection using the Open Data Kit platform. Electronic data collection templates were uploaded onto the tablets at the start of the survey and each time there was a form amendment. The questionnaires were available on the tablets in English, Chichewa (the main language of the Central Region) and Chitumbuka (the main language of the Northern Region), with the facility to toggle between the three languages at any time. Range checks and prompts were programmed into the forms. The tablets were charged overnight for field work with the battery lasting two working days. The tablets have integral GPS receivers which enable the fieldworkers to take co-ordinates. The tablets were also used to scan identification barcodes stickers. Specimen linking and other supporting forms were paper-based. These were double-entered in Access databases, verified and amended where necessary. A paper consent form record was also held.

Attempts were made to make contact with each individual listed in a household. It was recorded in the register if individuals in either area had left permanently, died, were ineligible (due to being under 18 or unable to give informed consent) or had already been included in the survey in a prior location. If individuals were not found at home, the household was revisited up to three times before the individual was recorded as “missed” in the register. “Bookings” were made through household members present to try to contact absent members. In the urban area, after the first 2 months of the survey, weekend working was instituted and at least one weekend visit had to be conducted before an individual could be marked as “missed”. Evening recruitment was considered, but not implemented due to security concerns. In a sample of urban enumeration areas, the approximate age of missed or refusing individuals was determined by interview of an informant or (for those refusing) the estimation of the interviewer in order to estimate the population age distribution and age-sex-specific participation rates. For those individuals found at home, informed consent was sought from all adults aged 18 and above residing in the study areas at the time of the main survey. For each person found a study identification number was assigned, whether or not the person consented. Each individual could consent separately for the main survey, the venepuncture and any sub-studies, as appropriate. For those that gave informed consent to take part in the survey, a questionnaire was administered including individual and household variables.

Anthropometric measurements; weight, height, waist circumference, hip circumference and mid upper arm circumference, were taken. After 30 min of inactivity, three blood pressure measurements, with 5 min resting time in between, were collected using portable electronic devices (OMRON Healthcare Co., Ltd. HEM-7211-E, Model M6), and the average of the last two readings was used, to allow for the phenomenon of raised blood pressure following activity or during unfamiliar procedures. Suspected hypertension was defined as systolic blood pressure of greater than or equal to 140 mm Hg and/or diastolic blood pressure of greater than or equal to 90 mmHg, or on regular antihypertensive medication. Participants were issued with a “health passport” (patient-held record used for outpatient clinical details in Malawi) if they did not already have one.

The participants were advised to fast overnight, for a minimum of 8 h, and the nurses returned the following morning (usually between 5 am and 8.30 am) to collect fasting blood samples and offer HIV screening using a rapid test. Diabetes was defined as fasting blood glucose of greater than or equal to 7.0 mmol/L, or on regular medication for diabetes, or a previous self-reported diagnosis of diabetes. Participants who had not fasted were re-visited once; if a fasting sample was not available the second time, then a non-fasted sample, together with details of the time of the last meal, was taken.

Formal laboratory tests on fasting samples, were used to determine blood glucose (FBG) and lipid profile from fasting blood samples. HbA1c was performed in a sample of individuals to investigate its utility as a diagnostic tool for diagnosis of diabetes in this population. Samples were batched daily and transferred to the respective laboratories the same morning. At each site, all assays were undertaken using two automated analysers (Beckman Coulter Chemistry analyzer, Model: AU480). The laboratories participate in an external quality control scheme (Thistle, RSA) and internal controls were conducted, exchanging samples between the two sites for repeat testing to ensure consistency of measurements.

Results of blood pressure screening and body mass index were recorded in the participant’s Health Passport. Overweight and obese study participants were counselled by the field staff on lifestyle modification. Study participants were referred to the government health institution within each of the sites, for confirmation of diagnosis and/or treatment when any abnormal health conditions (hypertension, diabetes, HIV) are identified, by means of a referral slip. Participants with suspected hypertension were notified and referred during the face-to-face interview process and were asked to wait for 3 days for any abnormal laboratory results before going to the clinic, unless hypertension was severe, in which case an urgent referral was made. Abnormal blood results were reported directly to the participants at home, and recorded in their health passports. Blood results within normal range were made available at the clinics and, in the urban area, delivered to the household on request.

All study participants who did not report to the clinic within 30 days of being referred, were visited at their home to ascertain reasons for not taking up referral.

In the urban site, Area 25 health facility had been flagged for establishment of a chronic care NCD clinic to relieve pressure on the central hospital outpatient clinic. This clinic was enhanced by deployment of a study clinical officer, a clinic clerk and nursing staff. In the rural health facility the same level of support was supplied to manage the increased demand for clinical consultations that had been anticipated as a result of the survey.

The study staff operated within the parameters of the MoH clinics, whilst logging and documenting attendances carefully. A study clerk received the patients at each of the clinics, and procedures were in place to identify study participants who omit to bring their referral slips. Donations of drugs were secured from CIPLA (first and second line oral formulations) for hypertension and diabetes, sufficient to supplement those available through MoH services and to ensure uninterrupted supply. The clinical staff managed referred survey participants and non-participants according to standard hypertension and diabetes treatment algorithms which are based on national treatment guidelines [30].

There is a commitment to continuing this service for 12 months after the completion of the survey prior to handover to MoH teams.

Each participant was given a unique study number that linked all the data collected on them in the survey, in each sub-study and laboratory results. A study identification number sticker was also placed in their “Health Passport” and on a referral slip if they were referred for care. In both urban and rural sites [22], spousal and household data linkages were created and stored. In the urban site health system electronic identity numbers [31, 32] were also collected, where available, from stickers on individuals’ health passports.

Patients attending for clinical care were registered using their study identification number.

After each data collection shift, the data were uploaded from the tablets into a MySQL database on a local project server. Check programs were then used to detect any problems such as duplicate identifiers. Clean data were then transferred into the main project MS Access database, also on the local project server. Original records were kept as an audit in a MySQL archive database. Daily, weekly and monthly backups were created and held off-site on secure servers.

Currently data are available only to study scientific staff and approved collaborators. As part of a major initiative to make programme data more accessible to regional scientists in training and the wider research community to maximise public health benefit, and through direct support from the Wellcome Trust, a major collection of these data will be made available in a suitably anonymised form on an open data platform after the primary analyses have been completed.

The enumeration or demographic surveillance datasets were merged with the study questionnaire, physical examination and laboratory result data and analysed using Stata 13. Data on missed participants from sampled enumeration areas were combined with participation data and demographic surveillance data to create age and sex categories for creating population distributions. Hypertension, diabetes, body mass index, alcohol use, smoking and household possession variables were used to explore the differences between participants who were found easily and those who were difficult to reach, by using logistic regression and adjusting for age and sex.

Ethical approval for the study was granted by the Malawi National Health Sciences Research Committee (NHRSC) protocol number #1072, and London School of Hygiene and Tropical Medicine (LSHTM) Ethics Committee protocol number #6303.

Data collection started in June 2013 and is ongoing at the time of this analysis. It is expected that the survey will be completed by July 2015.

In the urban area, enumeration was started 4 months in advance of the survey team, to allow full piloting of the enumeration procedures. Some areas enumerated were not included (on the rural periphery of the area) as the population was very scattered and was found to include farming communities. More recently, the survey took place immediately after the enumeration procedures. Time from enumeration to survey varied from 1 week to 11 months.

Data on participation are presented for the first 16 (of 21) study zones (regularly updated by demographic surveillance) to be completed in the rural area and the first 23 (of 35) study zones in the urban area. This represented 14,552 and 22,005 potential participants in rural and urban sites, respectively. However, only 11,066 individuals (from 6184 households) and 11,772 individuals (from 6619 households in the rural and urban areas (respectively) were approached. The rest were not found at home after three visits (1116 and 5729 respectively), had previously participated at another household, were ineligible, had died or had left permanently (Fig. 4).

In the rural area, of those found and asked to consent, 74.3 % were found on the first visit to the household, 19.7 % on the second visit and 6 % on the third. By study zone, the proportion found on first visit varied from 65 to 82 %. In the urban area, 77.8 % of participants were found on first visit, 16.1 % on the second and 5.9 % on the third. This varied across enumeration areas from 63.9 to 89.0 %. When stratified by site, there was no difference in the age distribution of those found on first, second or third visits although women were more likely to be found on a first visit than men.

In the urban area, 18.7 % of interviews with women and 28.0 % of interviews with men were undertaken at the weekend as the participants could not be found during the week.

96.7 % (10,709/11,066) of those approached in the rural are accepted to take part in at least one component of the study, compared to 91.8 % (10,693/11,772) in the urban area. All participants who consented to the interview were willing to have anthropometric and blood pressure measurements performed and all but 13 individuals answered questions about HIV testing history and ART status. In Karonga, 77.5 % of participants either consented to HIV testing or had consented to be tested in another recent study (Fig. 4). In Lilongwe testing was accepted by 58 % of participants. In Karonga 7.2 % of those who did not accept rapid testing self-reported to be HIV-positive, 15.9 % in Lilongwe. The acceptance rates for next-day biochemical tests; venepuncture collection for fasting glucose and lipid were in excess of 90 % at both sites although some who consented did not keep their next-day appointment (~5 %) (Fig. 4). More than 99.5 % of samples were collected from individuals who had reported to have fasted according to instructions.

The age and sex distributions of the total population in the rural area were estimated by combining data from individuals that participated in the current survey and known ages of missed individuals from available DSS data. In the urban area, the age distribution of missed individuals was estimated from specially sampled urban enumeration areas (data collected from household informants), and combined with survey participants data to compute total urban population distribution (Fig. 5). Precise comparison cannot be made as missing individuals in the urban area only had estimated ages, but overall the urban adult population was younger; median age for males (approximately 32 vs. 34 years) and median age for females (approximately 30 vs. 35 years) and had a lower female to male ratio (1.05:1) than in the rural area (1.2:1).

The lowest overall participation rates were in urban males (43.6 %) followed by urban females (75.6 %) then rural males (80.3 %) and females (93.6 %). Within urban males the age group 40–44 years (based on estimated ages of those not participating) had the lowest participation rate (28 %). Of those who participated in the survey, urban males were also least likely to accept venepuncture or HIV testing.

283 (4.6 %) of rural households did not participate at all (thus no household level data were available); 196 (68.6 %) of these were households with only a single adult. In the urban area 1084 (16.4 %) of households did not participate at all, 385 (35.5 %) were single adult households and 499 (46.0 %) had two adult members.

Direct comparison of socio-economic status between participants and non-participants across the two sites was not possible as there was no data on urban non-participants. The proportion of people missed varied from 5.5 to 16 % by study zone in the rural area. The two areas with the lowest proportion missed were both fishing communities. The proportion of people missed varied from 23 to 37 % by study zone in the urban site. The enumeration areas with the highest proportion missed were those with seasonal workers at the tobacco processing plants and areas with higher proportion of civil servants and wealthier individuals.

The mobility of the rural population in and out of the DSS is well-described [22] and household movements within the DSS are also well captured. Within the new urban study site, the variable delay between enumeration and survey capture gave an opportunity to measure the rate of movement there, although movements within the area cannot currently be distinguished from those moving outside the area. Those who had left their household between enumeration and survey varied from 3.2 to 38.1 % by enumeration area, which was linearly related to the time between enumeration and survey (Fig. 6). Of those who did participate, 15 % reported they had been resident in that property for less than 1 year. Younger people, females, and poorer people were significantly overrepresented in this group.

The study identification number system and referral system worked well, with 100 % identification and linkage of patients in clinic to survey data in both rural and urban site. The use of the health service electronic identity numbers in the urban area was less useful with only 1809 (10 %) of the participants being able, or willing, to provide a verifiable number when visited at their household.

To explore the importance of the lower participation rates and higher mobility, preliminary analyses were conducted to assess whether ease of recruitment (categorised as either found on first or subsequent visit), whether recruited on a weekday or weekend (urban area only) and duration of residence more than or less than 1 year (urban area), was associated with outcomes and risk factors (Table 1).

Adjusting for age and sex, those found on the second or third visit compared to the first visit were more likely to be overweight, current alcohol users and in the top two wealth quintiles. They were less likely to be current smokers. Those surveyed at the weekends were more likely to in the upper wealth bracket and alcohol users, and less likely to be smokers or be hypertensive. People who had been resident in their current property for less than a year were less likely to be overweight or to use alcohol than more permanent residents. These associations remained significant after adjusting for wealth quintile.