This study was conducted in the Nadowli District of Ghana. Farming accounts for about 85% of the labour force with maize, millet, groundnut and beans as some of the staples and relatively available all year round.
This study was cross-sectional in design, and was carried out among public servants in the Nadowli District. Public servants in this study refer to the totality of human resources employed by state or government departments established in accordance with the constitution of Ghana as public service, and those who are on government payroll within the Nadowli District. Women who were public servants but were pregnant at the time of the study were not included. At the time of this study, a total of 775 public servants were employed in a total of 12 public service departments in the district.
We focused on public servants in this study for a number of reasons. First, previous researchers have observed that public servants are an important group of interest when it comes to NCDs because, the lay public generally expect them to be leaders when it comes to living and practicing healthy lifestyles because of their relatively better access to information . At the same time, this group is also at risk of leading sedentary and unhealthy lifestyles partly due to long periods of sitting in work places, and partly because of their relatively better socio-economic status which makes it easier for them to access less physically active modes of transportation such as cars. Second, we focus on this group because less attention has been paid to them in research across Africa and in Ghana, despite the recognition that they could be at heightened risk of NCDs.
Sample size determination
We determined the appropriate sample size for the study using the Public Service of Creative System survey software (http://www.surveysystem.com). Using the population size of 775, with a confidence level of 95%, a sample size of 257 was obtained. However, 271 questionnaires were administered to cater for data entry errors and non-responses.
In terms of sampling, all the 12 public service departments within the district were listed and each department coded. The codes were folded and put in a basket and picked at random until half of them were picked. The subjects were selected through a proportionate random sampling. This sampling technique ensured the inclusion of greater number of respondents from bigger departments. This ensured that our sample was representative of all the different categories of public servants in the district. In order to select a respondent, any person who was present at the time of entering a particular department was interviewed and was asked to call the next available person. This was done in all selected departments until the total sample size was obtained.
Data collection instruments and procedures
We used structured questionnaires (see Additional file 1) to gather data on respondents’ socio-demographic characteristics such as age, sex, religion, occupation, marital status, health risk behaviours (smoking and alcohol consumption), nutrition knowledge/health and physical activity. Anthropometrics were measured for the calculation of their Body Mass Index. Respondents were weighed wearing light cloths and without shoes. We also measured height of respondents with a suspended microtoise tape to the nearest 1 m without shoes and in minimum clothing standing erect with hands hanging loosely by their sides.
Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Overweight/obesity was defined as BMI of ≥ 25 kg/m2; and obesity as BMI of ≥ 30 kg/m2.
Pretesting of data collection instruments
The questionnaire was pretested on selected number of public servants outside the sample area and necessary corrections and adjustments made. The pretest enabled all ambiguities in questionnaire items and responses to be identified and corrected. The pretest also helped to determine how much time was required to complete the questionnaire.
Data management and statistical analysis
The SPSS statistical software (version 20) was used to enter data, clean the data, and as well edit the data for inconsistencies. All questionnaires that were incomplete or did not meet other quality control tests were not included for analysis. Descriptive statistical analysis such as frequency and percentage distributions were first used to summarize the data as well as describe important characteristics of study respondents. Bivariate and regression analyses were then performed to examine the possible relationship between a number of independent variables such as age, sex, marital status, level of education and leisure time activity, and dependent variables such as BMI and Hypertension and Diabetes status. Statistical significance was held at 95% confidence level and at a p-value of < 0.05.
Measured blood pressure ≥140 mmHg systolic and/or ≥90 mmHg diastolic or self-reported use of drug treatment for hypertension irrespective of measured blood pressure .
Body Mass Index (BMI)
Normal range BMI (healthy weight) = 18.5–24.9 kg/m2; underweight <18.5 kg/m2; overweight = 25.0–29.9 kg/m2; obesity ≥0.0 kg/m2. These definitions were based on the WHO Classification .
The absence of non-vigorous physical activity for at least 30 min ≥5 days of a week or vigorous physical activity for 20 min in ≥3 days of a week.
Civil servants who self-reported current smoking of cigarettes.
Consumption of ≥5 drinks of alcohol at one sitting (males); and consumption of ≥4 drinks at one sitting (females).