In ternationa l Scholars Journa ls African Journal of Food Science Research ISSN 2375-0723 Vol. 7 (2), pp. 001-007, February, 2019. Available online at www.internationalscholarsjournals.org © International Scholars Journals Author(s) retain the copyright of this article. Full Length Research Paper Nutritional status of undergraduates in a Nigerian university in south-west Nigeria O. B. Adu1*, A. M. Falade 1, E. J. Nwalutu1, B. O. Elemo1 and O. A. Magbagbeola2 1 Department of Biochemistry, Lagos State University, P. M. B 1087, Apapa, Lagos, Nigeria. 2 Department of Biochemistry, College of Medicine, University of Lagos, Idi-araba, Lagos, Nigeria. Accepted 23 November, 2018 The study evaluated the nutritional status and eating habits of undergraduate students in a Nigerian University. One hundred undergraduates (ages 15 to 40 years) of the Lagos State University, Ojo participated in the study. General information, anthropometric data, as well as a 7-day dietary recall were obtained by means of questionnaire. Venous blood samples were collected from the respondents and analyzed for vitamins A and C, creatinine, zinc, iron, total and differential blood counts. Mean body mass index (BMI), mid arm circumference (MAC), vitamins A and C, iron (Fe), zinc (Zn) and creatinine concentrations were 24.56 ± 3.3 kg/m 2 , 26.7 ± 3.0 cm, 20.5 ± 14.3 µg/dl, 1.5 ± 71.27 µg/dl, 19.62 ± 5.65 µmol/L, 6.6 ± 1.9 mg/kg and 1.24 ± 1.53 µg/dl, respectively. Mean PCV, WBC and Hb were 39.2 ± 4.9%, 5.34 ±1.73 × 10 6 /L and 12.22 ± 1.93 g/dl, respectively. 53% of the respondents were over-weight; 6%, obese and 15% under weight. PCV, Hb and lymphocytes were significantly higher in males than in females. There was positive correlation between serum vitamin C and Zn concentrations (r = 0.203), Fe and Zn (r = 0.539), Zn and neutrophil (r = 0.210) and vitamin A and basophil (r = 0.559). There was however a negative correlation between Zn and eosinophil count. Number of meals and milk intake had no effect on the status of the subjects. However, fruit intake positively affected neutrophil count (r = 0.202); vegetable intake positively affected serum Fe concentration (0.256); and intake of nutritional supplements positively affected serum Zn concentration. Also, serum vitamin A concentration in both male and female students was low. Key words: Adolescent nutrition, anthropometry, body mass index, hematology, nutritional status, serum zinc, vitamin A status, undergraduates. INTRODUCTION Recent trends in the results of major examination in the country have indicated that there is a decline in academic performance of students at all levels (Ighodalo, 2004). This decline has been attributed to some major factors like poor academic background, attitude of students towards examinations and attitudes of teachers to work. Another remote cause of poor academic performance of students could be linked to the worsening socio-economic condition of the country, which has affected the *Corresponding author. E-mail: tosin.adu@lasunigeria.org. feeding habit of students (Ighodalo, 2004). Malnutrition is a major problem in both developed and developing countries and deficiencies in some nutrients have been reported to cause diseases which could lead to impaired cognitive development (Simeon and McGregor, 1989). Other studies have related lifestyle of students, particu- larly breakfast consumption, to their cognitive abilities as reflected in their academic performance (Pollit, 1982, 1987; Lisa, 1998). However, most of these studies have excluded young adults in the tertiary institution. In developing countries, many children with mild to mo- derate malnutrition survive to reach adolescence, when malnutrition tends to remain mild but chronic, being de- Table 1. Mean ± SD of some nutritional parameters of undergraduate students. Parameters Male (n= 41) Female (n= 59) Total (n= 100) Weight (Kg) 65.38 ± 10.43 a 63.54 ± 7.65 a 64.00 ± 9.09 Height (m) 1.66 ± 0.26 a 1.61 ± 0.18 a 1.63 ± 0.23 BMI (Kg/m 2 ) 24.19 ± 3.46 a 24.83 ± 2.92 a 24.53 ± 3.34 MAC (cm) 27.15 ± 3.22 a 26.58 ± 2.71 a 26.70 ± 3.00 Vitamin A ( /dl) 21.94 ± 12.7 a 19.41 ± 15.41 a 20.49 ± 14.34 Vitamin C (mg/dl) 1.73 ± 1.34 a 1.47 ± 1.24 a 1.57 ± 1.27 Iron ( mol/l) 19.64 ± 5.62 a 19.79 ± 5.70 a 19.62 ± 5.65 Zinc (mg/Kg) 6.79 ± 1.90 a 6.44 ± 2.09 a 6.57 ± 1.97 Creatinine (mg/dl) 1.05 ± 0.84 a 1.39 ± 1.88a 1.24 ± 1.53 PCV (%) 41.45 ± 3.80 a 37.56 ± 5.03b 39.22 ± 4.88 WBC (x10 6 /L) 5.68 ± 1.65 a 5.02 ± 1.77a 5.35 ± 1.74 Hb (g/dl) 12.95 ± 1.18 a 11.66 ± 2.22 b 12.22 ± 1.93 N (%) 66.15 ± 8.04 a 64.02 ± 9.08 a 64.95 ± 8.61 L (%) 26.31 ± 6.46 a 29.64 ± 8.24 b 28.21 ± 7.63 M (%) 3.15 ± 2.58 a 2.41 ± 2.00 a 2.69 ± 2.27 E (%) 3.49 ± 1.80 a 3.36 ± 2.25 a 3.46 ± 2.05 B (%) 0.05 ± 0.22 a 0.13 ± 0.38 a 0.09 ± 0.33 abV alues with different superscripts within row are statistically significant at P < 0.05). tectable only by anthropometric measurements. On the other hand, relatively well-nourished children may deve- lop malnutrition in adolescence as a result of acquired dietary habits, influenced by obsession with thinness (WHO, 1986; Matsuhashi, 2000; Ryan et al, 1998). Several studies, mainly from developed countries, have demonstrated that, despite the increasing trends in the prevalence of overweight and obesity, fatness phobia is common during adolescence, especially in females (Thompson and Chad, 2003; Jones et al., 2001; Weinshenker, 2002). Nutritional status is the combination of an individual’s health as influenced by intake and utilization of nutrients and determined from information obtained by physical, biochemical and dietary studies (Durning and Fidanza, 1985). Information on the nutritional status and dietary habits of the adolescent population in Nigeria is however scanty. This study was therefore intended to evaluate the nutritional status and eating habits of adolescents and young adults in a Nigerian University. MATERIALS AND METHODS Subject The study was conducted using undergraduate students of the Lagos State University, Ojo Campus. Subjects were randomly selected from across the 6 faculties on Ojo Campus. Subjects who had taken ill in the last 4 weeks and those currently on medication were exempted from the study. In the end, 100 students (ages 15 – 40 years), which included 41 males and 59 females participated in the study. Data collection Data on general information, socioeconomic status, and eating habits were obtained by the administration of structured question- naires. Anthropometric assessment was carried out according to the method of Scrimshaw and Gleason (1992). Dietary assessment was done using a 7 day dietary recall. Ten millilitre of venous blood was drawn from the forearm of the subjects and evenly divided into three bottles. One bottle contained EDTA and the two were plain bottles. The blood sample in the EDTA bottle was used for the haematological analysis and the other two bottles were centrifuged in a Haereus labofuge for 5 min at 2000 rpm. The serum obtained was used for the mineral and biochemical analyses. Analyses Packed cell volume (PCV), haemoglobin (Hb), total white blood cell (WBC) and differential white blood counts were determined accor- ding to the method described by Baker and Silverton (1985) . Serum creatinine was determined according to the modified Jaffe method using the creatinine kit (Quimica, SA). Serum vitamins A and C con-centrations were determined as described by Baker and Silverton (1985) . Serum iron (Fe) and zinc (Zn) concentrations were deter-mined by atomic absorption spectrophotometry using a Phillip PUX 1000 atomic absorption spectrophotometer. Statistical analyses Sample mean and standard deviation values were calculated and means were compared using student’s t test. Pearson’ correlation was used to test for association. All statistical analyses were done using the SPSS version 11.0 software. RESULTS Table 1 shows the values of some anthropometric, bio- chemical and haematological parameters of subjects. There was no statistical difference between male and female undergraduate students except PCV, Hb and lym- phocyte values which were significantly higher (p < 0.05) in male students. Age, BMI and MAC distribution of the undergraduates in this study are shown in Figures 1 to 3. 83% of the stu- dents’ populations were aged between 21- 25 years, 12% were 26-30 years, 3% were 15- 20 years and 2% were 31-40 years. 53% of the student populations were over- weight, 36% had normal weight, 15% were under-weight and 6%, obese. Only 3% of the student population in- volved in the study had MAC lower than normal (< 22 cm). Figure 4 shows the frequency of milk, fruit and veget- able and nutritional supplement intake by respondents. 41% of the students consumed milk daily; 24%, weekly, and 28%, occasionally. About 7% of the students did not take milk at all. Well over half (55%) of the respondents consumed fruit occasionally, 31% weekly and 11% daily. About 3% of them did not consume fruits at all. Consumption of vegetables was also low among the students. 50% of them consume vegetables occasionally; 39% of them, weekly and only 11% of them daily. Intake of nutritional supplements among the students was also very low. Up to 30% of them did not take any form of nutritional supplements, 44% took supplements occasionally and only 7% took their supplements daily. Table 2 shows the Pearson correlation values for some of the parameters measured. There was no corre-lation between milk and frequency of meals intake, and nutritional status of the students. However, there was a positive relationship between fruit intake and neutrophils count (r = 0.202); vegetable intake and serum Fe concen- tration (r = 0.205); and supplements intake and serum Zn concentration. There was also a positive correlation be- tween serum vitamin C and Zn concentrations (r = 0.203); Zn concentration and neutrophils count (r = 0.210); and vitamin A and basophil count (r= 0.559). Over 80% of the student population had low vitamin A concentration (<24 g/dl). DISCUSSION The present study is a preliminary report of ongoing efforts by the authors to elucidate from the nutritional point of view, the underlying cause of the increasing poor academic performance among undergraduates in tertiary institutions. Results from studies like this are important for effective policy formulation and implementation, especially where nutritional interventions are required. Previous reports (Ryan et al., 1992) have indicated es- sential roles of diet and nutrition in determining health status. A good number of the study population ate at least 3 meals daily, but the dietary recall showed that they ate mostly carbohydrates, with very little protein (data not shown) . This was in agreement with the report of Umoh (1977) in his study of nutritional and health problems in South-eastern Nigeria. BMI and MAC were used to assess leanness and these two parameters are indicators of the long term dietary history of the respondents. In this study, BMI value greater than 31.5 kg/m 2 was considered as an indication of obesity and below 18.0 kg/m 2 as leanness (WHO, 1995). Leanness as a result of under nutrition causes reduced metabolism, reduced energy production and non availability of free glucose which is both required for stu- dying and stress management. About half of the students who participated in the study (53%) were over weight, 6% obese and 15% underweight. Obesity has been asso- ciated with an increased propensity for the development of kidney, heart and circulatory diseases; diabetes and complications during pregnancy and child birth in females (Guthrie, 1979; Wardlaw and Kessel, 2002; WHO, 2003). A recent report (Cannon and Leitzmann, 2005) indicated a staggering rise of obesity in young people in middle income countries, and this has serious implications in later life. With the exception of serum vitamin A concentration, all other serum metabolites and haematological parameters were within normal range. Mean serum vitamin concen- tration for both male and female subjects was low. Consumption of fruits, vegetables and nutritional supplements among the undergraduates in the study was low. Consumption of fruits and vegetables among adole- scents between the ages of 12 and 19 years has been reported to decrease with age (AIHW, 2007). This trend could be as a result of waning parental influence as ado- lescents get into tertiary institutions or the problem of easy accessibility to these foods on the university cam- pus. This factor might also have contributed to the low vitamin A status of the subjects. The positive correlation between zinc and iron was contrary to previous reports (Solomon and Jacob, 1981) where ingestion of zinc and iron in various ratios led to reduced zinc absorption. Davidson et al. (1995) however reported that iron ingestion had no effect on zinc absorption. There was a positive relationship between Zn, vitamins A and C, and some cells of the immune system. Vitamin C, apart from having antioxidant activity, also helps in immune function. White blood cells which are the major immune cells contain the highest Vitamin C concentration of all body constituents (Wardlaw and Kessel, 2002). Several reports have also shown the im- portance of Zn in both specific and non specific immune responses (Cunningham et al., 1990; Shankar and Prasad, 1998). Over 80% of the subjects had low serum vitamin A con- F re q u e n c y 60 50 40 Fr eq ue nc y 30 Male 20 Female 10 0 15-20 21-25 26-30 31-40 Age (yrs) Figure 1. Age distribution of respondents by gender. 35 30 25 20 male 15 female 10 5 0 Underweight Normal Overweight Obese BMI range Figure 2. BMI distribution of respondents by gender. 50 45 40 35 F re q u e n c y 30 25 20 15 10 5 0 Below normal Normal MAC range Figure 3. MAC distribution of undergraduate students. 60 50 40 s u b j e c t s 30 o f N o 20 10 0 Daily Weekly Occasionally None Frequency of intake male female Above normal Milk intake Fruit intake Vegetable intake Nutritional supplement Figure 4. Frequency of milk, vegetables and supplement intake by respondents. Table 2. Pearson correlation between nutrient intake, nutritional and immunological status of undergraduates. Parameter Correlation Vitamin A Vitamin C Creatinine Zinc Iron N L M E B Pearson correlation -0.154 0.102 -0.034 -0.021 -0.055 0.071 -0.087 0.078 -0.065 0.002 No of meals Sig. (2-tailed) 0.133 0.313 0.735 0.838 0.593 0.484 0.388 0.443 0.518 0.983 N 96 100 99 97 97 100 100 100 100 100 Pearson correlation 0.011 0.035 0.022 -0.121 -0.051 0.057 -0.05 -0.026 -0.098 -0.003 Sig. (2-tailed) 0.917 0.73 0.831 0.238 0.55 0.575 0.624 0.798 0.333 0.974 Milk intake N 96 100 99 97 97 100 100 100 100 100 Pearson correlation 0.054 -0.038 -0.092 0.004 0.12 .202* -0.127 -0.104 -0.153 0.094 Fruit intake Sig. (2-tailed) 0.603 0.707 0.367 0.968 0.24 0.044 0.209 0.301 0.128 0.353 N 96 100 99 97 97 100 100 100 100 100 Vegetable Pearson correlation -0.023 0.056 -0.005 0.166 .256* -0.071 -0.006 0.057 0.004 -0.035 intake Sig. (2-tailed) 0.825 0.582 0.958 0.105 0.011 0.486 0.956 0.574 0.965 0.732 N 96 100 99 97 97 100 100 100 100 100 Supplement Pearson correlation 0.136 0.138 0.041 0.041 .221* 0.039 -0.031 0.093 -0.065 0.055 Intake Sig. (2-tailed) 0.187 0.169 0.686 0.686 0.03 0.703 0.756 0.358 0.523 0.584 N 96 100 99 99 97 100 100 100 100 100 Pearson correlation 1 -0.133 -0.115 -0.057 -0.107 0.004 -0.018 -0.035 0.128 .559** Vitamin A Sig. (2-tailed) 0.275 0.268 0.588 0.305 0.971 0.861 0.732 0.213 0 N 96 96 95 97 93 96 96 96 96 96 Pearson correlation -0.133 1 -0.094 .203* 0.097 0.082 -0.033 0.117 -0.167 -0.173 Vitamin C Sig. (2-tailed) 0.275 0.354 0.046 0.346 0.418 0.742 0.247 0.097 0.084 N 96 100 99 97 97 100 100 100 100 100 Pearson correlation -0.115 -0.094 1 -0.163 -0.148 0.162 0.162 0.002 0.045 0.051 Creatinine Sig. (2-tailed) 0.268 0.354 0.113 0.15 0.11 0.11 0.986 0.656 0.616 N 95 99 99 96 96 99 99 99 99 99 Pearson correlation -0.057 .203* -0.163 1 .539** .210* -0.119 0.067 -0.249* -0.107 Zinc Sig. (2-tailed) 0.588 0.046 0.113 0 0.039 0.245 0.517 0.014 0.298 N 97 97 96 98 97 97 97 97 97 97 Pearson correlation -0.107 0.097 -0.148 .539** 1 0.163 -0.052 0.003 -0.151 -0.164 Iron Sig. (2-tailed) 0.305 0.346 0.15 0 0.112 0.613 0.974 0.14 0.108 N 93 97 96 97 97 97 97 97 97 97 Pearson correlation 0.021 0.06 -0.008 0.027 -0.136 0.081 -0.091 0.173 -0.01 -102 PCV Sig. (2-tailed) 0.844 0.567 0.941 0.798 0.194 0.438 0.385 0.095 0.927 0.327 N 90 94 93 92 92 94 94 94 94 94 Pearson correlation 0.19 0.042 -0.063 -0.071 -0.189 .250* -0.264* 0.004 -0.082 0.146 WBC Sig. (2-tailed) 0.075 0.686 0.554 0.502 0.072 0.016 0.011 0.966 0.433 0.162 N 89 93 92 91 91 93 93 93 93 93 Pearson correlation 0.067 0.034 -0.009 0.004 -0.137 0.084 -0.099 0.121 0.026 0.018 Hb Sig. (2-tailed) 0.529 0.745 0.933 ..971 0.194 0.42 0.341 0.243 0.801 0.86 N 90 94 93 92 92 94 94 94 94 94 centration, despite the claims by most respondents that they took fruit, milk and vegetables regularly. Although these foods are good sources of the vitamin, the method of storage and processing and the adequacy of intake could be responsible for the low serum concentration. Vitamin A deficiency has been associated with non- accidental blindness, impairment of growth and immunity and follicular hyperkeratosis (Wardlaw and Kessel, 2002). Nutritional education and intervention therefore is expedient in order to prevent cases of visual impairment among the students. Conclusion There was a high incidence of over weight and vitamin A deficiency among the student population. In curbing this trend, there is therefore an urgent need for sustained nutritional education among young adolescents. REFERENCES AIHW (2007). Profile of Nutritional Status of Children and Adolescents. Cat. no. PHE 89. Australian Institute of Health and Welfare, Canberra. Baker FT, Silverton RE (1985). Introduction to Medical Laboratory Tech- nology, 6 th ed, Butterworth, London pp. 320-335. Cannon G, Leitzmann C (2005). The new nutrition science project. Public Health Nutr. 8: 673-694. Cunningham RS, Bockman RS, Lin A, Giardina PV, Hilgartner MW, Caldwell-Brown D, Carter DM (1990). Physiological and pharmacological effects of zinc on immune response. Ann. New York Acad. Sci. 587: 113-122. Davidson L, Almgren A, Sandstrom B, Hurrell RF (1995). Zinc absorp- tion in adult humans: the effect of iron fortification. Br. J. Nutr. 74: 417 – 425. Durnin JVGA, Fidanza F (1985). Evaluation of Nutritional Status. Biblthca Nutr. Dieta 35: 20-30. Guthrie HA (1979). Introductory Nutrition. 4 th edn. The CV Mosby Company, St. Louis p. 503. Ighodalo D (2004). Reasons for yearly weakness observed in WAEC candidates. Punch Newspaper p. 48. Jones JM, Bennett S, Olmsted MP, Lawson ML, Rodin G (2001). Disordered eating attitudes and behaviours in teenaged girls: a school-based study. Can. Med. Assoc. J. 165: 547-552. Lisa MS (1998). The correlation between eating breakfast and school performance. Am .J. Clin Nutr. 65: 7795-9845. Matsuhashi Y. (2000).Thinness: drives and results. J. Adolesc. Health 27: 149-150. Pollit E, Lewis NS, Garza C, Shulman R (1983). Fasting and cognitive function J. Psychiatr. Res. 17: 168-174. Pollit E, Watkins WE, Husaini MA (1997). Three month nutritional sup- plementation in Indonesia infants and toddlers, benefit child memory function 8years later. Am. J. Clin. Nutr. 66: 1357-1363. Ryan SA, Craig LD, Finn SC (1992). Nutrient intakes and Dietary Pat- terns of Adult Americans. A National Survey. Gerontol. Soc. Amer. M145-M150. Ryan YM, Gibney MJ, Flynn MA (1998). The pursuit of thinness: a study of Dublin schoolgirls aged 15 y. Int. J. Obes. Relat. Metab. Disord. 22:485-487. Schrimshaw NS, Gleason OR (1992). Rapid Assessment Procedures. Qualitative Methodologies for Planning and Evaluation of Health Related Programmes Int. Nutr. Foundat. Dev. Countries. Boston. Shankar AH, Prasad AS (1998). Zinc and immune function: the biological basis of altered resistance to infection Am. J. Clin. Nutr. 68:447S-463S. Simeon DT, Grantham–McGregor SM (1990). Nutritional deficiencies and Children’s behaviour and mental development. Nutr. Res. Rev. 3: 1-24. Solomon NW, Jacob RA (1981). Studies on the bioavailability of zinc in humans: effects of heme and non heme iron on the absorption of zinc. Am. J. Clin. Nutr. 34: 475-482. Thompson AM, Chad KE (2003). The relationship of social physique anxiety to risk for developing an eating disorder in young females. J. Adolesc. Health 31: 183-189. Umoh Z (1977). Nutritional and health problem in southern eastern Nigeria. Nig. Med. J. 2: 56-57. Wardlaw GM, Kessel M (2002). Perspective in Nutrition 5 th edn. McGraw – Hill. London p. 322. Weinshenker N (2002). Adolescence and body image. School Nurse News. 19:12-16. World Health Organization (1986). Young people’s health. a challenge for society; report of a WHO Study Group on Young People and Health for All by the Year 2000.. Geneva: World Health Organization. Technical Report Series No. 731, 1-117. World Health Organisation (1995). Field Guide on Rapid Nutritional Assessment in Emergencies, WHO, Regional Office for Eastern Mediterranean, Alexandria. World Health Organisation (2003) . Diet, Nutrition and the Prevention of Chronic Diseases. Report of a Joint WHO/FAO Expert Consultation. WHO Technical Report Series No 916. Geneva.