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

Abstract

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.

Introduction

Non-communicable diseases (NCDs) are the leading causes of death in the world (WHO, 2010) and in South Africa (Pillay-van Wyk et al., 2016; Statistics South Africa, 2017). Low and middle income countries are undergoing a rapid epidemiological transition characterised by a shift from disease burden dominated by communicable disease and childhood illnesses to non-communicable disease such as type 2 diabetes mellitus, and cardiovascular disease which affects all age groups (Beaglehole et al., 2011; Mahmood et al., 2013; Gouda et al., 2019). These developing countries are experiencing the fastest rising prevalence of non-communicable diseases with more devastating outcomes compared with high income countries (Islam et al., 2014; Juma et al., 2019).  The worldwide data reported that NCDs accounts for 80% related death in low and middle income countries (Maimela et al., 2016).

In South Africa, the occurrence of NCDs burden has increased over the past years resulting in an estimated 37% of all-cause mortality and 16% of disability-adjusted life years (Alberts et al., 2005; Puoane et al., 2012). Nojilana et al. (2016) and Bradshaw (2001) revealed that mortality due to NCDs is similar in all province of South Africa, even though the causes may differ. Most risk factors of NCDs are often categorised as behavioural or biological (Hoy et al., 2013; Maimela et al., 2016). Behavioural risk factors such as low income, age, smoking, unhealthy diet, stress, consumption of alcohol and sedentary life style are considered as major modifiable risk factors for non-communicable diseases. Kraja et al. (2016) revealed that tobacco use, alcohol consumption, physical inactivity, unhealthy diet, and obesity are the behavioural risk factors for non-communicable diseases and many others account for 80% of mortality. Studies on the prevalence of such risk factors had been carried out in urban and rural villages around South Africa (Wandai and Day, 2015; Maimela et al., 2016; Manning et al., 2016).  Bearing in mind that the causes of NCDs may differ we conducted a study on the prevalence of behavioural risk factors in Collins Chabane municipality of Vhembe District.

Methodology

The study was conducted in Collins Chabane municipality, which is one of four municipalities of Vhembe District. The Collins Chabane Local municipality is a Category B municipality situated within the Vhembe District in the far north of the Limpopo Province. The municipality shares borders with Musina in the north, Thulamela in the north-east, the Mopani District in the south, and Makhado in the west. It is making up 20% of its geographical area. It was established by the amalgamation of portions of the Thulamela and Makhado Local Municipalities in August 2016. The municipality is predominately rural-based with only one town. The massive development of modern shopping centres with all the well-known chain stores presented which could lead to lifestyle changes lead to the selection of this municipality. Simple random sampling was used to Collins Chabane from the four municipalities in Vhembe District. The municipality has an estimated total population of 347974 (Stats SA, Community Survey, 2016). Of the total population, 36.4%, 58.5% and 5.1% are population under 15, between 15 and 64, and over 65 respectively (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/m²) 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/m² (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.

Results

Table 1 provides the socio-demographic characteristics of males and females. About 32.1% of the participants were between the age of 18-25 years while 25.2% were between the age of 26-35 years. Majority (58.7%) of participants had secondary education while 16.9% had tertiary education and only 14.6% had primary education. Most (60.3%) of participants were single while 22.2% were married. Majority (76.2%) of the participants were unemployed while 23.8% were employed.  Of all participants who were working, 10.6% were self-employed while 8.2% worked at the government and 4.9% worked in the private sector.

About 12.4% of the participants were suffering from health condition in the current study. Of all participants who suffered from health condition, only 9.7% suffered hypertension while 2.4% diabetes and only 0.3% suffered cancer (Table 2).

About (24.4%) of participants consumed alcohol in the current study. The prevalence of alcohol consumption was higher in male (22.8%) as compared to (1.6%) female counterparts. Only 16.7% of participants consumed alcohol at the age of less than 19 years.  Of all the participants who consumed alcohol only 22.7% consumed beer. In addition, only 18% of the participants engaged in binge drinking. However, 13.9% of the participants consumed alcohol because of peer pressure.  Only 12% of the participants consumed alcohol on weekend (Table 3).

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).

About 12.5 % of males and 16.0 % of females met the recommended daily allowance of carbohydrates while the majority 53.9% of males and 57.7% of females consumed over required amount of carbohydrates. Furthermore, most males (66.4%) and 73.2% of females consumed over required amount of protein. Only 17.1% of males and 16.9% of females met the recommended daily allowance of fats while the majority 60.5% of males and 53.1% of females consumed excessive amounts of fats (Table 7). 

About 40.8% of males and 39.4% of females consumed excessive amount of energy while 34.9% of males and 28.6% of females consumed over required amount of energy. About 45.5% of males and 50.7% of females consumed over required amount of sugar. Only 17.1% of males and 16.0% met the recommended daily allowance for dietary fibre while 53.9% of males and 47.9% of females consumed over required amount of dietary fibre. Furthermore 36.2 % of males and 26.3% of females met the recommended daily allowance for sodium while 34.2% of males and 32.4% of females over consumed the recommended amount of sodium (Table 8).

Males

BMI negatively correlated with protein (r = -0.007; p =0.932). Protein strongly correlated with energy (r = 0.823; p = 0.000), total fats (r = 0.830; p = 0.000), carbohydrates (r =0.587; p =0.000) and total sodium (r =0.666; p = 0.000). Energy strongly correlated with total fat (r =0.817; p = 0.000), carbohydrates (r = 0.877; p= 0.000), total dietary fibre (r = 0.663; p =0.000) and sodium (r =0.724; p=0.000).

Females

BMI negatively correlated with total protein (r= -0.007;p=0.914) and total fat (r=-0.089;p=0.197).Total protein strongly correlated with energy (r =0.827;p=0.000),total fat (r =0.741;p=0.000),carbohydrates ( r =0.582;p=0.000) ,total dietary fibre (r =0.503;p=0.000) and sodium (r=0.620;p=0.000).Energy strongly correlated with total fat( r=0.795;p=0.000),carbohydrates (r =0.875;p=0.000),total dietary fibre ( r=0.720;p=0.000) and sodium ( r=0.766 :p=0.000) (Table 9).

Significance difference between males and females

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

Significant relationship between gender and alcohol consumption

There is a significant relationship between gender and alcohol consumption.

 , (1, N=365) =126.299, p =0. 000.Gender is dependent upon alcohol consumption. Males are 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 = 0.587

4.11.2 Significant relationship between gender and physical activity

Gender is significantly associated with physical activity.

 , (4, N =365) = 29.849, P =0.000.

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 overburdened economy of South Africa. Despite South Africa prohibiting the advertising and promotion of tobacco according to The Tobacco Products Control Act 83 of 1993, our study found a very low prevalence (13.9%) of cigarette smoking among male participants. Similarly, Maimela et al. (2016) and Thorogood et al. (2007) reported the lower prevalence of cigarette smoking at 13% and 14% respectively in rural areas. However, Agaku et al (2012) reported high prevalence of tobacco use among South Africans males. About 10.1% of the male participants in the current study initiated smoking at the age of less than 19 years. Congruently, The Surgeon General Reports (2012) revealed that majority of adults’ smokers initiated the habit of smoking before the age of 18 years. It is estimated that about 15 million premature death in the world is attributed to smoking and 4 million of these deaths were in men.

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

Declarations

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.

Authors’ contributions

SC, NT, NN and MR collected the data. MNS analyzed the data. MSA, SC, NT, NN, MR and MNS contributed materials/analysis tools. MSA prepared the draft manuscript. MSA and MNS finalized the manuscript and provided a critical review. All authors have read and approved the final manuscript.

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.

Competing interests

The authors declare that they have no competing interests.

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Tables

Table 1: Socio-demographic data of study participants

Table 2: Health condition of the study participants

Table 3: Alcohol consumption of study participants

Table 4: Nutritional status of the study participants

Table 5: Physical activity index of the study participants

Table 6: Cigarettes use

Table 7: Energy, protein and fats RDA of the study participants

Table 8: Energy, Total Sugar, total dietary fibre and sodium RDA of the study participants

Table 9: Correlations between BMI and dietary intake of males and females.

 Table 10:  Significance difference between males and females