Association Between Dietary Consumption, Anthropometric Measures And Body Composition Of Rural And Urban Ghanaian Adults; A Cross Sectional Study.


 Background Overweight and obesity have become threats to public health in all regions across the globe including sub-Saharan Africa where prevalence used to be low. Policies to regulate the food environment and promote healthy food consumption look promising to reducing the prevalence obesity but in Ghana there is not enough data to elicit a policy response. This study assessed the association between dietary consumption, Body Mass Index (BMI) and body composition among rural and urban Ghanaian adults.Methods This was a cross-sectional study involving 565 Ghanaian adults. Structured interviewer-administered questionnaires were used to collect information on socio-demographics. Dietary consumption was assessed using household food frequency questionnaire and 24-hour recall. Height, weight, BMI, waist circumference and body composition of all participants were determined. Mann Whitney U test was used to analyze differences in anthropometric measures, body composition and consumption among rural and urban participants. Principal component analysis was used to analyze household food frequency data. Chi-square was used to measure differences in obesity prevalence by community and gender. Multinomial logistic regression was used to model the risk factors associated with obesity.Results The prevalence of overweight and obesity using BMI were 29.9 and 22.9 respectively. Use of waist circumference measurement resulted in the highest overall obesity prevalence of 41.5%. Prevalence of obesity was higher among females compared to males across all measures with the exception of visceral fat that showed no significant difference. Four different patterns were derived from principal component analysis. Vegetable convenience dietary pattern showed significant negative correlation with visceral fat (r=-0.142, p 0.002), body fat (r=-0.102, p 0.209) and BMI (r=-0.136, p 0.003). Multinomial logistic regression revealed that males (OR 21.968, CI 10.876-44.373, p-value < 0.001) and rural participants (OR 1.684, CI 1.039-2.729, p-value <0.05) had higher odds of being of normal weight.Conclusion Prevalence of overweight and obesity continue to rise in Ghana, especially among females. Public education and screening as well as interventions that regulate the food environment and makes affordable and available healthy food options are needed to control the rise in obesity prevalence.

and makes affordable and available healthy food options are needed to control the rise in obesity prevalence.

Background
Obesity is a major cause of cardiovascular and chronic diseases which contribute to about 71% of all global deaths [1]. Obesity continues to increase across all ages and regions all over the world and children are also an important risk group [2]. In sub-Saharan Africa where about 42% of the population live below the poverty line, prevalence of obesity continues to rise although a strong positive association has consistently been observed between socio-economic status and obesity [3].
Annually, about 2.8 million people die from overweight or obesity [1]. Once a problem of the developed world, obesity is now on the increase in developing countries and Ghana is no different. It is forecasted that by 2030, obesity will be more prevalent in developing countries [4] and Dake [5] projects prevalence among Ghanaian women aged 15-49 years to reach 15.1% by 2023. Developing countries are faced with a double burden of disease not only at country and community levels but also within households. This implies that in a household where adults are obese, it is possible to find undernourished children who struggle to achieve optimum growth z-scores for their age [1]. Stunting and wasting are risk factors for obesity in later years and this situation creates a cycle of malnutrition in the sub region [6].
Genetic susceptibility, high socio-economic status, excess caloric consumption among other factors predict obesity but the current transition and trend is mainly driven by increased caloric intake and reduced physical activity levels that are associated with urbanization coupled with lack of policies to control an obesogenic food environment [7,8]. Urbanization leads to reduced consumption of healthy staples and an obesogenic food environment makes readily available cheaper priced energy dense foods [9]. Energy balance is key to the maintenance of body weight and consumption of more calories than what is utilized through metabolic and physical activities leads to weight gain. These excess calories, stored in the body as fat can impair proper health and function [10]. Additionally, inadequate intakes and deficiencies of micronutrients such as zinc are linked to obesity [11].
Consistently, studies have reported a higher prevalence of obesity among urban populations compared to rural ones. Part of this may be due to differences in physical activity levels, socioeconomic status and food consumption patterns among rural and urban dwellers [12,13]. Gender differences have also been observed with females been more susceptible than males. Parity is one factor that puts women at higher risk than men [14,15].
Body mass index is the usual screening tool for determining obesity among populations [15]. Build-up of body fat positively correlates with total body mass and hence weight gain indices are used as determinants of body fat [16]. It however, has limitations of not been able to accurately predict adiposity [17]. BMI, when used in combination with other diagnostic tools such as waist circumference and Body Impedance Analysis (BIA) provides in-depth information about adiposity as well as presumed cardio-metabolic risk. Increased body fat is a prominent risk factor for type 2 diabetes, stroke, hypertension and heart disease [18,19]. Combining these tools to screen for obesity among populations may reveal higher prevalence than what is reported by most studies.
In Ghana, some studies have been conducted within various populations to ascertain the prevalence of overweight and obesity but these studies have mainly focused on urban females [5,20]. Most of these studies have also been done in Greater Accra region which is the capital of Ghana. An example is the Women's Health survey which found a 62.2% prevalence of overweight and obesity among urban women living in Accra [20]. Few studies have assessed consumption patterns associated with obesity, compared rural and urban individuals as well as included body composition measurements.
Assessment of all these parameters will provide more insight in to the obesity menace and consumption patterns associated with it.
The main aim of this study was to compare the prevalence of obesity among rural and urban dwellers using BMI, waist circumference and body composition measures and to determine consumption factors associated with obesity.

Methods
This was a cross-sectional study that involved the use of interviewer-administered structured questionnaires to collect information on socio-demographics. Sociodemographic data collected included age, sex and level of education. Weight, height, waist circumference and body composition measurements of all participants were taken. The height of each participant was entered in to the body composition analyzer which was used to measure the weight and other body components. BMI was generated from the weight and height measurement (weight in kilograms/ height in metres 2 ).

Study site
The study was conducted in two communities in the Ashanti region of Ghana; Ahodwo an urban community and Ejuratia a rural community. Data collection was done by visiting households within the selected communities

Sample size and sampling
The study involved a total of 565 participants. Systematic sampling was used to select households and any household member either male or female eighteen years and above was included. One household was randomly selected within each house. For each household, only one member was included and where there were both a male and a female who qualified, the male was selected to ensure gender balance as it was more difficult to find males in households. For the rural community after a random start, every third house qualified to be included in the study and every fifth house was chosen for the urban community. The difference in intervals was due to the smaller sample frame in the rural area compared to the urban area. Households who declined to participate in the study were excluded.

Dietary consumption
Twenty four-hour recall and household food frequency was used to collect information on food consumption. The household food frequency consisted of commonly consumed food groups with specific foods listed under each food group. Participants were also asked of any likely food under each of the food groups they had consumed that were not captioned. Participants were to indicate how often they consumed each food item. One twenty-four-hour recall was taken for each participant to assess previous day food consumption. Nutrient analysis template; a food composition table consisting of only Ghanaian foods was used to estimate nutrient intakes and dietary diversity from the 24-hour recall.

Body composition and anthropometric measurement
Participants were made to remove their footwear and put on light clothing prior to the taking of anthropometry. Height was taken using Seca stadiometre, model 213 with participants standing up right with feet together and hands at the sides. Weight and body composition were measured using the Omron body composition monitor, model HBF-514. Height, gender and age of participants were entered into the body composition monitor before participants were made to stand on it. This generated body composition results as well as BMI of participants. Body mass index (kg/m 2 ) was classified using WHO criteria for adults; < 18.5 underweight, 18.5-24.9 normal, 25-29.9 overweight and > 30 obese. Visceral fat of > 9% was definitive of central obesity and body fat cut offs were based on gender and age of participants as suggested by Gallager [19,21]. Waist circumference was taken with a flexible tape measure. Central obesity was defined as waist circumference of >88cm for females and > 102cm for males.

Ethical clearance
Ethical clearance for the study was granted by the Council for Scientific and Industrial Research (CSIR), Ghana; RPN 011/CSIR-IRB/2017. Written permission was sought from local government officials before data collection and all participants signed an inform consent form to indicate voluntary participation.

Statistical Analysis
Statistical Package for Social Sciences (IBM SPSS) 23 was used for data analysis. Normality test revealed that data was positively skewed. Mann Whitney U test was used to compare the median age, body composition and nutritional intakes among rural and urban participants. Kruskal Wallis test was used to compare the median nutrient intakes among underweight, normal, overweight and obese participants. Spearman correlation was used to determine the relationship between BMI and body composition measures. Principal component analysis was used to determine the patterns of consumption. Multinomial logistic regression was used determine the predictors of obesity measured by waist circumference. Waist circumference was used because it determined the highest prevalence of obesity and strongly correlated positively with all other body composition measures. A p-value of < 0.05 was set as statistically significant.

Results
A total of 565 participants took part in the study; 292 from rural and 272 from urban. The median age of participants was 40(26) years and there was no statistical difference between rural and urban participants. The overall median body mass index of participants was 25.6(7.4) with urban dwellers recording a significant higher value. Visceral fat was also significantly higher for urban dwellers compared to rural participants. Calorie, carbohydrate and fibre intakes were significantly higher among rural participants while urban participant consumed higher vitamin A. Other nutrients did not show any significant difference. Table 1 shows socio-demographics, nutritional intake and body composition characteristics of study participants. Using BMI, there was no difference in the prevalence of obesity among rural and urban participants.
Visceral and body fat cut offs showed a higher prevalence of obesity in urban compared to rural participants. Prevalence of obesity by all parameters was higher among females compared to males with the exception of visceral fat that showed no difference.         *controlled for age and gender Table 9 shows a partial spearman correlation adjusted for age and gender between waist circumference, BMI and body composition measures. All variables showed significant correlations but the strongest correlations were between visceral fat and BMI r = 0.905(p<0.001), body fat and BMI r = 0.851 (p<0.001) and BMI and waist circumference r = 0.845(p<0.001).  Table 10 shows multinomial logistic regression for risk factors of central obesity determined by waist circumference. Multicollinearity was checked and carbohydrate and fibre had strong correlations with energy intake and protein respectively and were therefore excluded from the model. The obese group was set as reference for the outcome variable and urban and female were set as reference for the explanatory variables, community and gender respectively. Males had about 22 times odds of being normal compared to females at p-value <0.001. Rural dwellers had odds of about 1.7 times of being normal compared to urban participants and this was significant at p<0.01.

Discussion
This study evaluated the association between nutrient consumption and body composition of rural and urban adults in Ghana. The study had a higher number of female participants compared to males and this was because it was mostly females who were met at the households. This finding that is comparable to reports from the 2014 Ghana Demographic and Health survey [22]. The prevalence of overweight and obesity using BMI was 29.9% and 22.9% respectively with a total prevalence of 52.8%. The prevalence of overweight and obesity found in this study is comparable to what has been reported by some studies even though others have reported slightly higher or lower prevalence [22][23][24][25]. Several studies have reported a significantly higher prevalence of obesity by BMI among urban compared to rural dwellers but in this study, no significant difference was found [23,26]. This implies that rural communities are gradually catching up with urban communities and there is therefore the need for further investigation and interventions to curb this menace. Total energy and carbohydrate intake were significantly higher among rural compared to urban participants. Though not statistically significant, sugar and saturated fat intake was higher among the urban sample. This finding supports data on high availability and consumption of sugary foods in urban centres and higher consumption of staple foods among rural dwellers [27]. Additionally, multinomial logistic regression results from the study indicates that rural communities are associated with normal weight compared to urban centres.
This calls for policies that will regulate the availability of sugary foods notably sugar-sweetened beverages in urban communities as these are associated with weight gain and risk of type 2 diabetes.
Central obesity determined by visceral fat was higher among urban participants; central obesity is highly associated with cardiovascular diseases and poses a higher cardiometabolic risk compared to generalized obesity [18,19].
Prevalence of obesity determined by BMI, waist circumference and body fat were higher among females compared to males. Most studies have also reported a higher prevalence of obesity among women compared to men though most of these studies have only used BMI [28,29]. In this study where visceral fat, BMI, total body fat and waist circumference were used, prevalence across all determinants was significantly higher for females compared to males with the exception of visceral fat that showed no significant difference. Several factors put women at higher risk of obesity compared to men. Sedentary behavior such as long hours watching television and parity have been documented to cause weight gain in women [30]. Even though pregnancy and childbirth are associated with weight gain and retention it is possible for women to lose almost all the weight gained during pregnancy and child birth [30,31]. This calls for post-natal education and interventions to empower women to avoid obesogenic behaviors post-partum which are thought to aid in lactation but are rather fattening. High occurrence of obesity among women is related to adverse pregnancy outcomes such as pre-mature delivery and low birth weight babies. Low birth weight is a risk factor for obesity in adulthood and this trend has led to developing countries experiencing a double burden of disease [32]. The prevalence of central obesity was also higher among females and this also puts them at risk of chronic non-communicable diseases. High amount of total body fat is associated with elevated blood pressure and this was higher among women compared to men [30]. Multinomial logistic regression also revealed that female gender poses a significant risk to the development of obesity. Several interventions have been tailored toward socio-economic empowerment of women in Ghana but findings from this study calls for more interventions to be implemented to address the health challenges of women and also empower women toward taking charge of their health in order to achieve optimal health status.
Fat, protein, sugar and carbohydrate contribute to total energy intake and caloric intake positively associates with BMI. The intakes of the aforementioned nutrients were higher among obese participants and this was associated with higher intakes of micronutrients but not with higher dietary diversity score. Principal component analysis revealed four different patterns. Pattern 1 which comprised sugar sweetened beverages, egg, milk, instant noodles, processed meat among others showed a significant positive correlation with body mass index and body fat. This is not surprising as the component consisted of foods like sugar sweetened beverages, processed meat, commercial bread, pasta and vegetables. Frequent and high intakes sugar sweetened beverages, sweets, margarine, confectionery processed meat, instant noodles, pasta and meat promote obesity [30].
These findings call for the regulation of processed foods that currently dominate and make the food environment obesogenic.
Waist circumference is a reliable tool for determining abdominal obesity. Its strong positive correlation with other body composition measures supports the reliability of waist circumference as a measure of obesity and adiposity. This simple measurement can be used as a diagnostic tool to assess obesity and adiposity among populations and in clinical practice.

Conclusion
This study indicates that overweight and obesity continue to rise in Ghana, especially among females.
Prevalence of obesity determined by BMI was similar among rural and urban dwellers. Interventions that regulate the food environment and makes affordable and available healthy food options such as vegetables are needed to control the rise in obesity rate and prevalence.

Limitation
This study was cross-sectional and hence conclusions about risk factors of obesity may be limited.
drafted the manuscript. Elizabeth Catherine Swart and Charles Apprey critically revised the manuscript. All authors have read and approved this final draft for submission