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

Abstract

Background

The prevalence of adolescent obesity is rising in all parts of the world, but only very few studies have considered factors influencing obesity among Nigerian adolescents. This study therefore aimed to determine the prevalence of obesity and its association with socio-demographic profile, lifestyle factors, dietary patterns and physical activity patterns among in-school adolescents in Southwest, Nigeria.

Method

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.

Result

There were 211 (52.8%) males and 189 (47.3%) females, with mean ages of 14.8 ± 2.1 and 14.4 ± 1.9 years respectively. The prevalence of overweight/obesity was 12.8%, and the associated factors were age, sex, class, the number of children in the family, birth orders and the dietary pattern dominated by starchy foods, roots and tubers (p < 0.05). However, no significant relationship existed between adolescents’ obesity and lifestyle factors, as well as physical activity patterns (p > 0.05). After controlling for confounders, age, number of children and birth orders remained significant.

Conclusion

The prevalence of overweight/obesity was relatively high among the respondents, and this was associated with the age, number of children in the family and the birth order of the adolescents. The findings of this study underscore the importance of family planning to the control of the obesity epidemic in Nigeria.

Background

Obesity is a public health problem resulting from a long-term imbalance between food intake and energy expenditure.[1, 2] It is a global problem that affects 50 million girls and 74 million boys worldwide. Also, 213 million children and adolescents, and 1.3 billion adults were in the overweight range worldwide.[3] What was once considered a disease of the developed countries, is now a potential health problem in developing countries.[4–6] In 2016, more than 70 percent of overweight/obese people lived in low and middle-income countries.[7, 8] In Sub-Saharan Africa, the prevalence of overweight and obesity increased by almost a third between 1992 and 2005.[6]. Unlike childhood obesity that has plateaued in many high-income countries, [9–11] adolescent obesity has increased substantially around the world [12, 13]. The prevalence rates are as high as 15.6 percent for overweight and 4.9 percent for obesity among 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 [21–25]. Also, unhealthy dietary intake, such as a high intake of refined carbohydrate foods, saturated fats, sugar, and low dietary fibre intake [26–29] 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, 32–35]. 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.[38–41] More studies are required to elaborate on the influence 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 profile, lifestyle factors, dietary patterns and physical activity patterns among in-school adolescents in Southwest, Nigeria.

Materials And Methods

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 semi-urban 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 first 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 final stage, the respondents were selected using stratified random sampling technique, with stratification 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 first 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, cross-tabulations 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 significantly 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 inflections of the scree-plot of eigen-values construction (Fig. 2) and the percentage of total variance explained. The reliability of the factor analysis was verified using the Kaiser–Meyer–Olkin (KMO) test with a sampling adequacy of 0.9 and Bartlett’s test of sphericity significant 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 confidential and participants were identified using only serial numbers.

Results

There were 211 (52.8%) males and 189 (47.3%) females, with mean ages of 14.8 ± 2.1 and 14.4 ± 1.9 years respectively. Most of them were of the Yoruba ethnicity (92.5%), were Christians (73.5%) by religion and were living with both of the parents (81.5%). As for the risky lifestyle of the adolescents, 28 (7.0%) had smoked before, 7 (1,8%) currently smoked, 66 (16.5%) had taken alcoholic beverages before and 20 (5.0%) were currently taking alcoholic beverages. While majority (93.0%) of the respondents did not know, 12 (3.0%) and 16 (4.0%) knew that their fathers and mothers had hypertension respectively. Sixteen (4.0%) and 6 (1.5%) also reported a history of diabetes in their fathers and mothers respectively.

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 BMI-for-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 first component (PCI), which accounted for 35.3% had the largest positive loadings for fruits, vegetables, meat, poultry, eggs and products, fish 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 profile is as shown on Table 2. Age (p < 0.001), sex (p = 0.038), class in the school (p = 0.003), number of children in the family (p = 0.003) and birth order of the child (p = 0.005) were the factors that were statistically significant. There was no statistically significant relationship between obesity and physical activity pattern (χ² = 0.107, p = 0.743), and all the lifestyle factors (p > 0.05). The second component (PC2) dominated by high carbohydrate/starchy foods and legumes was significantly associated with obesity (P = 0.033), while the others were not.

All independent variables that had a statistically significant 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 significantly 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.[45–47] 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 significantly higher in the early adolescence period. This finding 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 findings 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 significantly 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 significantly associated with adolescent obesity even after controlling for confounders in the present study. A similar finding 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 finding 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 first or second child is associated with adolescent obesity, with first and second child being 8 times more likely to be overweight/obese compared to those who birth order is greater than 4. Studies have reported similar findings with a higher risk of overweight with being the only child.[62, 63] These findings underscore the importance of family planning to the control of the obesity epidemic in Nigeria.

Studies have demonstrated that significant relationship exists between physical activity and body weight gain [64–67], suggesting that sedentary lifestyle plays a role in excessive weight gain. However, our result showed that no significant relationship exists between physical activity patterns and body weight gain. This finding was in agreement with similar results reported by other researchers [68, 69] who worked among adolescents. The discrepancy in these results may be attributable to the different sample sizes, and the populations studied. It was, however, noted that only one respondent in the present study could be classified as having high physical activity with nearly 3 out of 10 having low physical activity. This pattern of reduced physical activity among adolescents should be discouraged. All the stakeholders including the government, school authorities and parents should put measures in place to discourage sedentary lifestyle and encourage increased physical activity among adolescents.

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 confidentiality, 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 significantly associated with obesity. The dietary pattern rich in starchy foods, roots and tubers was also significantly associated with obesity among the adolescents. Obesity had no significant 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 significantly 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 findings of this study also underscore the importance of family planning to the control of the obesity epidemic in Nigeria.

Abbreviations

BMI Body mass index

CI Confidence interval

FFQ Food Frequency Questionnaire

KMO Kaiser–Meyer–Olkin

LGA Local Government Area

LIE Local Inspector of Education

OR Odds ratio

PCA Principal Component Analysis

QFFQ Quantitative Food Frequency Questionnaire

SPSS Statistical Package and service solutions

WHO World Health Organization

Declarations

Declarations

Ethics approval and consent to participate

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 confidential and participants were identified 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.

Competing interests

The authors declare that they have no competing interests

Funding

This research was funded by the authors

Authors’ contribution

AAA conceived and designed the study while MDO, SY, AA, and RA make a substantial contribution in the implementation phase. All authors were involved in data collection, analysis and interpretation. All authors read and approved the final manuscript.

Acknowledgement

We appreciate all the parents of the participants, and the students for their cooperation throughout the data collection phase. Also, we are grateful to the school management and the Head Teachers for their invaluable contributions and support.

AAA and MDO were supported by the Consortium for Advanced Research Training in Africa (CARTA). CARTA is jointly led by the African Population and Health Research Center and the University of the Witwatersrand and funded by the Carnegie Corporation of New York (Grant No–B 8606.RO2), Sida (Grant No:54100029), the DELTAS Africa Initiative (Grant No: 107768/Z/15/Z). The DELTAS Africa initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa's Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust (UK) and the UK government. The statements made and views expressed are solely the responsibility of the Fellows.

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