Adolescent Obesity and its association with socio-demographic prole, lifestyle factors, dietary and physical activity patterns; ndings from southwestern Nigeria

The prevalence of adolescent obesity is rising in all parts of the world, but only very few studies have considered factors inuencing obesity among Nigerian adolescents. This study therefore aimed to determine the prevalence of obesity and its association with socio-demographic prole, lifestyle factors, dietary patterns and physical activity patterns among in-school adolescents in Southwest, Nigeria. A total sample size of 400 in-school adolescents was selected through a multi-stage sampling technique from secondary schools in Ile-Ife. The dietary patterns were assessed using a 92-item QFFQ, while the activity patterns were assessed using the physical activity questionnaire for older children and adolescents. Data were analyzed using IBM SPSS.

adolescents in the European countries. [14] In Sub-Saharan Africa, the prevalence of 10.6 percent and 2.5 percent for overweight and obesity have been documented. [15]. In Nigeria, the prevalence of overweight and obesity among adolescents ranges from 1.0-8.6 and 0.0-3.0 percent respectively. [16,17] While genetic factors are estimated to cause more than 40 percent variation in Body Mass Index (BMI), [18,19] environmental factors contribute immensely to obesity epidemic. [20] Studies have showed that socio-demographic variables such as age, sex, education level, wealth and marital status are determinants of obesity [21][22][23][24][25]. Also, unhealthy dietary intake, such as a high intake of re ned carbohydrate foods, saturated fats, sugar, and low dietary bre intake [26][27][28][29] have been shown to be associated with increased rates of overweight and obesity. Evidence has also shown that sedentary lifestyles, smoking and alcohol could be risk factors for obesity. [30,31] In Nigeria, most studies on obesity focused on women and children. It is important to study obesity in adolescents because of its health implications in them. Obesity in adolescence is associated with several adverse health consequences for the entire life course. It is associated with a higher risk and earlier onset of chronic diseases such as type 2 diabetes, cardiovascular diseases and cancer [30,[32][33][34][35]. Also, it has adverse psychosocial consequences and lowers educational attainment [36,37].
The few studies on adolescent obesity in Nigeria focused mainly on the prevalence, with little or nothing on the determinants. [38][39][40][41] More studies are required to elaborate on the in uence of different factors on adolescent obesity as this will inform effective prevention and intervention programmes. This study therefore aimed to determine the prevalence of obesity and its association with socio-demographic pro le, lifestyle factors, dietary patterns and physical activity patterns among in-school adolescents in Southwest, Nigeria.

Study location and study population
The study was carried out among in-school adolescents (10 to 19 years old) in Ile-Ife, which is a semiurban town in Southwestern part of Nigeria. Adolescents who were acutely ill, had chronic illnesses that could affect their weight (like sickle cell disease anaemia) and those with disabilities that made them unable to stand were excluded from the study.

Sample size and sampling technique
The sample size was calculated to get an absolute precision of ± 5% using STATCALC on the Epi-Info software. The proportion of expected outcome was taken as 37.2% which was the proportion of in-school adolescents with obesity from a previous study in Ile-Ife, with an acceptable margin of error of 5%. The calculated sample size was 359, but was adjusted for an anticipated non-response of 10%, giving a sample size of 400. Four hundred adolescents were therefore recruited from 6 secondary schools in Ile-Ife using multi-stage sampling technique. Two Local Government Areas (LGAs) were selected from the 5 in Ile-Ife using simple random sampling technique (balloting method) at the rst stage. At the second stage, 3 schools each were selected from the list of schools in the selected LGAs. The number of respondents to be selected in each of the schools was determined using proportional allocation. At the third and nal stage, the respondents were selected using strati ed random sampling technique, with strati cation along the line of the different classes.

Research instruments and data collection methods
A pre-tested structured questionnaire was used for data collection using the assisted self-administered method. The dietary patterns were assessed using 92-item quantitative food frequency questionnaire (QFFQ), while the activity patterns were assessed using the physical activity questionnaire for older children and adolescents by Kowalski et al [42], which has been validated and used among similar age group in Nigeria. [43] The instruments for anthropometric measurements were be the Seca® electronic bathroom weighing scale (SECA GmbH & Co, Germany) for measuring weight in 0.1 kilograms (kg). Height was measured to the nearest 0.1 meter using the stadiometer (Leceister® Height Measure, Seca, UK). The anthropometric measurements were done according to standard protocols recommended by the International Society for the Advancement of Kinanthropometry. [44] Data Management Data were analyzed using IBM SPSS version 23. Descriptive analysis of all the variables measured were rst done, and the categorical variables were reported as frequencies and proportions/percentages, while the continuous variables were reported as means ± standard deviation. At bivariate level, crosstabulations were done to test for associations between the different categorical variables (in line with the objective of the study) using the chi-square test. Fisher's exact test was used when there was an expected value was less than 5. T-test for 2 independent samples was used to compare the means of the continuous variables between the 2 categories of the dependent variable (Obese/Not obese). Logistic regression was used to control for confounders and to identify the predictors of obesity out of the independent variables that were signi cantly associated with obesity at the bivariate level.
Overweight and Obesity were determined using BMI-for-age Z-scores from the WHO reference charts > + 1 to + 2 and obese > + 2 respectively, and the 2 groups represented obesity in this study.
The responses to the questions on activity patterns were scored, and each of the sections was scored over 5. Afterwards, all the scores from the different sections were scored over 5. The scores were then categorized into < 2, 2.00-3.99 and ≥ 4 for low, moderate and high physical activity patterns respectively. [42] Principal Component Analysis (PCA) was done to reduce the dimension of dietary intake to a small number of dietary patterns. Factors were retained and interpreted for further analysis based on their natural interpretation, visual in ections of the scree-plot of eigen-values construction (Fig. 2) and the percentage of total variance explained. The reliability of the factor analysis was veri ed using the Kaiser-Meyer-Olkin (KMO) test with a sampling adequacy of 0.9 and Bartlett's test of sphericity signi cant at p < 0.001.

Ethical considerations
Ethical clearance was obtained from the Ethical Review Committee, Institute of Public Health, Obafemi Awolowo University, Ile-Ife. Permission for the study was obtained from the Local Inspector of Education (L.I.E.) of the selected local government and the Management of the selected schools. Written informed consent was obtained from parents and the adolescents who were 18 years or above, while assent was obtained from respondents younger than 18 years. All information gathered was kept con dential and participants were identi ed using only serial numbers.
After the scoring of the responses for the physical activity, the mean score was 21.5 ± 5.1, with a range of 10.0 to 39.6, out of a maximum score of 45. The respondents were then categorized into low, moderate and high using these scores ie 110 (27.5%), 289 (72.3%) and 1 (0.3%) respectively. Using the WHO BMIfor-age references, 51 (12.8%) of the respondents were overweight or obese. (Fig. 1) The 92-dietary items on the FFQ were regrouped into 16 dietary groups as seen in Table 2. Three dietary patterns which explained about 52% of the total variance (total dietary variability) were retained, using PCA. The rst component (PCI), which accounted for 35.3% had the largest positive loadings for fruits, vegetables, meat, poultry, eggs and products, sh and milk. The second component accounted for 9%, and had largest positive loadings for cereals and grain products, starchy fruits, roots and tubers, grain legumes, nuts and seeds. The third component accounted for 7.5%, and had positive loadings for nuts and seeds, fats and oils and condiments and spices. (Table 2).   The relationship between obesity and socio-demographic pro le is as shown on Table 2 All independent variables that had a statistically signi cant relationship (p < 0.05) with obesity at the bivariate level were entered into a binary logistic model. (Table 3). Age (p < 0.001), number of children in the family (p = 0.014) and the birth order of the child (p = 0.002) were the factors that remained signi cantly associated with obesity afterwards.

Discussion
The prevalence of overweight and obesity combined in this study is 12.8%, which is higher than what some authors had previously reported in Southwestern Nigeria. [45][46][47] Several other recent Nigerian studies have reported similar or even higher rates for overweight/obesity among Nigerian adolescents.
[38, 48-52] This rising prevalence of obesity among Nigerian adolescents should be a thing of concern to all stakeholders in adolescent health. A quick response to stem this tide therefore becomes necessary to prevent the associated health conditions which can result in lower quality of life in adulthood.
This study showed that the prevalence of obesity was signi cantly higher in the early adolescence period. This nding corroborates earlier studies that similarly observed higher prevalence rates of overweight and obesity in lower adolescent ages. [47] The reason could be as a result of the increase in hormonal secretion which accompanied the growth spurt at this time, and often may be responsible for the excess fat deposition. [53] The present study also found that females were more likely to be obese compared to males. Similar ndings have been documented previously in studies done among adolescents. [46,47] Differences in hormonal secretion, [53,54] lower involvement of females in rigorous physical activities and the cultural preference for girls [55] are some of the possible reasons that have been adduced by different researchers. However, other studies showed a higher prevalence among males compared to females. [13,56] These difference may be due to the age distribution and/or culture of the different study areas.
The dietary component dominated by carbohydrate/ starchy foods and roots and tubers foods were signi cantly associated with adolescent obesity. Studies have shown that consumption of carbohydrate/ starchy foods are associated with weight gain. [57,58] The high glycemic index of the food may play a vital role in weight gain. Conversely, higher consumption of whole grains, legumes, nuts, fruits and vegetables have been associated with a lower risk of chronic non-communicable diseases and obesity [59,60]. There is therefore a need for nutritional education intervention programmes for adolescents, especially within the school systems.
The number of children in the family remained signi cantly associated with adolescent obesity even after controlling for confounders in the present study. A similar nding showed that a few siblings are a risk factor of overweight/obesity,[61] whereas more numbers lower the risk for overweight.
[62] A possible explanation for this nding is that additional siblings might increase cost for food and general upkeep of the children, thereby limiting the average spending on food per child. Another probable explanation is that increased number of children increases the child's play, thereby increasing physical activity which has been shown to be protective. This study also shows that being the rst or second child is associated with adolescent obesity, with rst and second child being 8 times more likely to be overweight/obese compared to those who birth order is greater than 4. This study is not without any limitations. Since the dietary habits of respondents was self-reported, it is prone to social desirability bias or recall bias. This was however minimized by assuring the respondents of absolute con dentiality, and taking only a 30-day recall. The study was descriptive cross-sectional in design, therefore cannot be used to infer cause and effect.

Conclusion
This study found that the prevalence of overweight/obesity was relatively high among the respondents. Among the socio-demographic factors, age, gender, class, number of children and birth order were signi cantly associated with obesity. The dietary pattern rich in starchy foods, roots and tubers was also signi cantly associated with obesity among the adolescents. Obesity had no signi cant association with physical activity patterns and the lifestyle factors among the respondents. After controlling for confounders, age, number of children in the family and the birth order of the children remained signi cantly associated with obesity. Effective nutrition education is needed to change dietary habits that are detrimental to adolescents. The school authority should also check the availability of unhealthy foods within the school environment. The ndings of this study also underscore the importance of family planning to the control of the obesity epidemic in Nigeria. Awolowo University, Ile-Ife. Permission for the study was obtained from the Local Inspector of Education (L.I.E.) of the selected local government and the Management of the selected schools. Written informed consent was obtained from parents and the adolescents who were 18 years or above, while assent was obtained from respondents younger than 18 years. All information gathered was kept con dential and participants were identi ed using only serial numbers.

Consent for publication
Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Figure 1
Distribution of the Prevalence of obesity among the respondents according to age and sex.

Figure 2
Scree plot of eigen-values after Principal Component Analysis