Behavioural risk factors for non-communicable diseases amongst adults aged 18 years and above in Collins Chabane Municipality of Vhembe District in Limpopo Province, South Africa

Background : Tobacco use, alcohol consumption, physical inactivity, unhealthy diet and obesity are the behavioural risk factors for non-communicable diseases. To determine behavioural risk factors for non-communicable diseases amongst adults aged 18 years and above in Collins Chabane municipality of Limpopo province, South Africa. Methods : This study included 365 participants recruited from Collins Chabane municipality of Vhembe district, Limpopo province, South Africa. Municipality was selected using simple random sampling and convenience sampling was used to choose participants. Anthropometric measurements were measured following standard techniques. Data on dietary intake was collected using Food Frequency Questionnaire. Permission and clearance were obtained and participant’s rights were respected. Results : About (24.4%) of participants consumed alcohol in the current study. Males were more likely to consume alcohol as compared to female counterpart (54.6% vs. 3.3 %) Gender has a large effect on alcohol consumption. Cramer’s V = 0.58. The prevalence of alcohol consumption was higher in male (22.8%) as compared to (1.6%) female counterparts. The prevalence of underweight, overweight and obesity was 7.7%, 29.8%, and 11.3%, respectively. Majority 61.1% of the participants had sedentary lifestyle in the current study. About 13.9% of the participants smoked cigarette in the current study. Of all participants who smoked cigarette 10.1% initiated smoking at the age of less than 19 years Conclusion : Behavioural risk factors such as smoking, alcohol consumption, consumption of over required amount of sugar, sodium, protein, energy, carbohydrates, excessive fats intake, physical inactivity, overweight, obesity exist among people in Collins Chabane municipality.

(Statistics South Africa Community Survey, 2016). Convenience sampling was used to select three hundred and sixty-five participants. Data was collected during a three-month (March to May 2018) period by a team of health professionals (a nutritionist and a biokineticists). Participants were aged between 18 and above, consented and were present on the day of data collection. Participants who were in wheelchairs were excluded due to the lack of equipment to measure their weight and height, and those with psychological and mental diseases who are unable to recall and/or give correct data or information required. Data was collected using a questionnaire with four sections namely physical activity level, alcohol and tobacco use, weight and height, and Food Frequency Questionnaire. An expert from the Department of Linguistics at the University of Venda translated the questionnaire into the local language used in Collins Chabane which is Xitsonga and Tshivenda. Anthropometric assessments were performed according to standard procedures as described by the International Society for the Advancement of Kinanthropometry. The following measurements were taken in duplicate using calibrated equipment with the adult wearing light clothing and no shoes: standing height and weight.
Height was measured to the nearest 0.1 cm using a calibrated portable stadiometer and weight was measured to the nearest 0.01 kg on a portable Seca solar scale (model 0213) (Seca, Hammer Steindamm, Hamburg, Germany). The solar scale and stadiometer were calibrated before measurements using a calibration weight and steel tape respectively (Lee and Nieman, 2010).

Food survey
Food Frequency questionnaire was used to assess the dietary intake of pregnant mothers.
The adequacy of nutrients intake was compared with the recommended dietary intake for pregnancy (Food and Nutrition Board, 2011).

Definition of underweight, Normal, Overweight and Obesity
The BMI (Kg/m 2 ) was selected to estimate the prevalence of underweight, overweight and obesity according to WHO references values. Underweight was defined as less (<) 18.5, normal weight: 18.5 to 25, Overweight: 25-29.5 and Obesity: >30 kg/m 2 (WHO, 1995).

Statistical Analysis
Statistical package of social sciences (IBM SPSS Statistics., Armonk, NY version 24) was used to analyse categorical and descriptive data such as mean, standard deviation, frequencies and percentages. Spearman's correlation coefficients were used to compare relationship between variables. For comparison of gender, the Independent t-test was used. A p≤0.01 and p≤0.05will be considered statistically significant. Food finder was used to analysed dietary intake of the study participants.  Table 3).

Results
The prevalence of underweight, overweight and obesity was 7.7%, 29.8%, and 11.3%, respectively. The prevalence of overweight was higher in female (21.1%) as compared to 8.7% of male counterparts. In addition, females (2%) were more obese as compared to male (9.3%) ( Table 4). About 46% of female had sedentary lifestyle as compared to their male counterparts (15.1%). Furthermore, male (13.2%) had not good enough as compared to 9.1% of females. However, only 3.6% of males had very active as compared to (1.0%) of females (Table 5).
About 13.9% of the participants smoked cigarette in the current study. Of all participants who smoked cigarette 10.1% initiated smoking at the age of less than 19 years. Only 9% of the participants smoked cigarette 1-5 times per day. However, 20.4% of the participants were exposed to tobacco (Table 6).  (Table 7).  (Table 8).

Significance difference between males and females
There was a significant difference between males and females in terms of BMI as the pvalue is less than 0.005 (Table 10).

Significant relationship between gender and alcohol consumption
There is a significant relationship between gender and alcohol consumption.
Gender has a large effect on alcohol consumption. Cramer's V = 0.587
Gender is dependent upon physical activity. Males are more likely to be physical active than the female counterpart (10.5% vs. 1.9%), the results also reveal that females are more likely to leave sedentary lifestyle than males. Gender has a small effect on physical activity. Cramer's V= 0.286

Discussion
In this study, we focused on behavioral risk factors such as alcohol consumption, cigarette smoking, physical inactivity, nutritional status, dietary intake. This behavioral risk factors are also the risk factor for hypertension and diabetes which could put burden on the The prevalence of underweight, overweight and obesity was 7.7%, 29.8%, and 11.3%, respectively. The prevalence of overweight in the current study was higher than the prevalence (18.1%) reported by Motadi et al (2017) in Mopani district while that of obesity was lower. The results are higher than the provincial prevalence of 4.8% (overweight) and 3.3% (obesity). The prevalence was higher in female as compared to their male counterparts. However, the prevalence was lower when looking at provinces with Limpopo having 24% and 32.6% compared with 21.

Limitation Of The Study
Data was based on self-reports and may be affected by potential under-reporting especially on smoking and alcohol. The study was a cross sectional and didn't follow participants for a period. Some of the behavioural risk factor such as dietary intake may vary seasonally and might not be the representative. This data may not be the representative of Vhembe District as it focused on one municipality.

Conclusion And Recommendation
Behavioural risk factors such as smoking, alcohol consumption, consumption of over required amount of sugar, sodium, protein, energy, carbohydrates, excessive fats intake, physical inactivity, overweight, obesity exist among people in Collins Chabane Municipality. Due to nutrition transition and liberalisation which makes people access fast food due to market globalisation which leads to a change in dietary patterns, it is recommended that measures to control risk factors at rural areas should include awareness on consequences of consuming fast foods, physical inactivity, overweight and obesity.

Abbreviations
NCDs: Non-communicable diseases BMI: Body Mass Index

Acknowledgments
The authors would like to acknowledge the University of Venda and students from the Department of Nutrition and Biokineticists for assisting with data collection. Furthermore, we would like to pass our message of appreciation to participants residing in Collins Chabane Municipality for their participation and cooperation.

Funding
This research study received no funding.

Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on request.

Ethical consideration
Ethical clearance for the study was obtained from the University of Venda Research Ethics Committee (SHS/ 18NUT/07/1906) and the permission to conduct the study was granted by the Limpopo Provincial Department of Health Research Committee. The study was performed in accordance with principles of the Declaration of Helsinki (2008), Good Clinical Practices and the laws of South Africa. A full and adequate oral and written explanation of the study was given to the participants. Participants gave written signed informed consent to participate in the study. The consent form included the participants's right to withdraw from the study and codes were used to ensure confidentiality of the information obtained.

Consent to publication
The manuscript does not contain any individual person's data in any form.