Obesity is one of the leading preventable causes of death worldwide. ( 1 ). The World Health Organizations (WHO) technical report series of 1995 indicated that body weight significantly impacts an individual's health and disease status ( 2 ). Bakari et al., in 2007, reported these abnormalities of body weight to be expected in two suburban communities in Northern Nigeria at the rates of 13.1% for obesity, 18.5% for overweight and 6.7% for underweight ( 3 ). Data on obesity have been commonly reported in the past among specific risk groups, such as hypertensive and diabetic populations, many of which are hospital-based studies ( 4 , 5 ). Other community-based studies that are now emerging have been reported among rural or semi-urban dwellers ( 6 ).

Obesity, defined by the World Health Organization as a Body Mass Index (BMI) ≥30 kg/m ² , has become an epidemic dimension in the world, with Nigeria also having its share of the burden, as reported by Akarolo- Anthony et al.( 7 ). This current trend of obesity has been attributed to the socio-economic and epidemiological transition of Nigeria from a lower income country to a middle-income country, resulting in the change of lifestyle behaviors and dietary intake. As a result, many Nigerians now live sedentary lifestyles while consuming a diet with excess calories, as observed by Iloh et al ( 8 ). Lopez et al.( 9 ), reported CVD in developing countries causes twice as many deaths as HIV, malaria, and tuberculosis combined. According to earlier speculation, almost all unexpected deaths of medical origin in Nigeria are due to cardio-vascular causes. The association among dyslipidemia, obesity and hypertension is well established ( 10 ), and all are major risk factors for the development of CVD, a leading cause of visits to physicians and cause of death. Dyslipidemia is becoming increasingly common in Africa.

Some studies ( 11 , 12 ) claim that leptin serum concentrations in healthy individuals positively correlate with body fat content but correlate negatively when energy intake is reduced, and energy stores in fat are declining. Leptin levels are correlated positively with several endocrine substances, such as insulin, glucocorticoid, thyroids, and testosterone, as observed by Chu et al.( 13 ). Similar studies also indicate that it may mediate some endocrine-related processes, like the onset of puberty ( 14 ). Chu et al.( 13 ), suggested that impaired or modified receptor function may be associated with certain medical conditions other than obesity, such as cardiovascular disease and certain types of cancer. Research findings also indicate that leptin can act as a growth factor in the fetus and the neonate. It has been reported that obesity is a significant risk factor for the development of diabetes mellitus ( 15 ).

Remnant cholesterol is primarily chylomicron and VLDL, from which most triglyceride has been removed, such that each remnant particle contains about 40 times more cholesterol than LDL ( 16 ). According to a study, high remnant cholesterol is more predictive of myocardial infarction than any other lipid particle ( 17 ). Remnant cholesterol is significantly predictive of coronary artery disease in patients with normal total cholesterol ( 17 , 18 ).

Varbo et al. ( 19 ) suggested that remnant cholesterol was a mediator from obesity to ischemic heart disease; part of the higher risk of ischemic heart disease seen in obese individuals was explained by higher remnant cholesterol concentrations. However, it is currently unknown whether there is an association between high concentrations of remnant cholesterol as a mediator between obesity and a high risk of developing cardiovascular disease and leptin as a mediator in the development of obesity found in average weight, overweight, and obese individuals alike.

This is a cross-sectional study designed to compare the serum level of Leptin, some lipid fractions, and Remnant Cholesterol in normal, overweight, and obese participants. Based on the calculated sample size, 90 consenting participants that fulfilled the inclusion criteria were randomly recruited for the study. Informed consent from the participants was sought and obtained before enrollment into the study. Ethical approval was obtained from the Ethics Committee (NAUTH/CS/66/VOL.11/154/2018/088) of Nnamdi Azikiwe University Teaching Hospital Nnewi, and informed consent was sought from participants. Questionnaires were administered and served as a primary instrument for this study. The questionnaires were structured to reflect the health issues relevant to the study's objectives; the study comprised 90 obese and non-obese subjects, who were picked by non-probability sampling. Among them, 30 participants were known obese, 60 participants were non-obese, and between 20-50 years. The participants were labeled Normal weight (BMI 18.5-24.9 kg/m ² ), over-weight (BMI 25-29.9kg/m ² ) Obese (≥30kg /m ² ). BMI was measured as weight in kilogram 0.01 divided by height squared (m ² ), WC was measured with a tape to the nearest 0.1cm at the end of a normal expiration at the midpoint between the subcostal plane and the iliac crest of an exposed abdomen. HC was measured at the largest standing horizontal circumference of the buttock to determine the waist-to-hip ratio (WHR=WC/HC). Hypertension was defined as systolic blood pressure ≥140mmHg, and diastolic blood pressure ≥90mmHg. A fasting blood sample was obtained in the morning between 08:00-09:00 h, about 7ml, through venipuncture from each participant. Aliquots were drawn into a fluoride oxalate container for plasma glucose estimation, and later on, a non-fasting blood sample was obtained from the participants, and aliquots were drawn into plain tubes and allowed to clot at room temperature. The quantitative determination of serum leptin was performed using the sandwich Enzyme-Linked Immunosorbent Assay (ELISA). Technique, with commercially available reagent kit MONOCENT. Leptin (sandwich) ELISA, (CAT no: EL9-1059) (LOT no: 200610) by Monocent USA. The fasting lipid profile was assessed using commercially available kits (Randox). Serum total cholesterol and high-density lipoprotein HDLc were determined by the cholesterol oxidase method by Allain et al. ( 20 ) and serum triglyceride by glycerol kinase Trinder ( 21 ), and LDLc was calculated using the Friedwald formula( 22 ). Furthermore, Remnant Cholesterol was calculated using the formula. Rc=Tc-HDLc- LDLc by Dave-Feldman (2017). Fasting plasma glucose was determined using the enzymatic colorimetric method of Trinder ( 21 ). Statistical analysis was performed to compare the two groups using ANOVA. The values were expressed as the Mean±S.D. Values were regarded as significant if p was ≤ 0.05. Pearson correlation coefficient was used to correlate the parameters estimated.

Table-1 shows the mean anthropometric markers of all participants. There was no significant difference in the diastolic and systolic blood pressures. There was a significant increase in the body mass index of all the participants (p<0.001). There was a significant difference in the participants' waist-to-hip ratio. Table 2; shows the mean of the various fasting biochemical parameters of obese, overweight, and normal weight groups. A significant change was observed in the fasting plasma Triglyceride (TG) and very low-density lipoprotein (VLDL). (p<0.001) in the obese subjects when compared with the corresponding control values. No significant change was observed in other lipid parameters. Table 3; show the mean of the various non-fasting biochemical parameters of obese, overweight, and normal weight group. A significant change was observed in the non-fasting plasma Triglyceride (TG) (p<0.004) in the obese subjects when compared with the corresponding control values. No significant change was observed in other lipid parameters. Table 4; Show the mean serum leptin, remnant cholesterol, and fasting blood sugar in the obese, overweight, and normal-weight participants. There was a significant difference in the serum leptin level between the normal-weight participants (0.25±0.26) and overweight participants (0.51±0.27) at (P<0.003). There was a significant difference between the normal weight (0.25±0.26) and obese participants (0.63±0.29; p<0.001). There was no difference in the mean RC between the obese and overweight compared to the control. There was statistical significance in the fasting blood sugar level between the normal weight participants (3.46±0.79) and overweight (4.46±1.82) at (P<0.021), Also between the normal weight and obese participants (3.46±0.79 vs. 4.94±1.26) at (P<0.001). No difference was observed in the level of the calculated remnant cholesterol among the groups. Table 5 shows the Pearson correlation of leptin association and remnant cholesterol in groups; there was no significant correlation of leptin with remnant cholesterol in the groups as shown. Normal weight (r=-0.088; p<0.648), overweight (r=-0.081; p<0.701) and obese (r=-0.107; p<0.611).

Leptin expression and secretion correlate with body fat and adipocyte, as Sone et al. ( 23 ) reported. Leptin reduces appetite and body weight. The paradoxical co-existence of obesity and hyperleptinemia suggests the pathology of leptin resistance. High levels of leptin were observed in obese participants (0.63±0.29μg/l) than in average weight(0.25±0.26μg/l; p<0.001. There was an increased significant difference in the leptin level between the overweight (0.51±0.27μg/l) participants when compared to the average weight (0.25±0.26μg/l) participant at p<0.003. Reports from different study populations have demonstrated that serum leptin concentrations are elevated in human obesity in proportion to the degree of adiposity. ( 24 , 25 ). This increase in leptin correlated with the BMI and WHR parameters in all the obese and overweight participants. This is also corroborated by the study conducted by Masoud et al. ( 26 ), who also reported a significantly high level of leptin in obese subjects. Considine et al. ( 11 ) observed 4 times increased serum leptin levels in obese subjects compared to non-obese subjects and a significant direct association of serum leptin with BMI. This has been related to the assertion that obesity may be partly due to leptin resistance. From our results, there is an increased level of remnant cholesterol level in the groups in average weight (0.50±0.28 mmol/l), overweight (0.69±0.46 mmol/l), and obese (0.72±0.4 mmol/l) participants above the projected reference range and percentile (0.48 mmol/l) by Varbo et al.( 19 ), this shows that race might have a role in the pathophysiology of atherosclerosis induced by remnants cholesterol. There was no significant statistical difference in the level of remnant cholesterol among the groups. This shows the association of remnant cholesterol and cardiovascular disease is not caused only by adiposity, it can be explained by remnant cholesterol's ability to cause atherosclerosis in the arterial wall, which is a process that has been assumed to be driven by remnant cholesterol concentration in the bloodstream, independent of it a reason for elevations in overweight and obesity, this finding is in correspondence with Varbo et al., ( 27 ). The other lipid fractions, fasting TG and VLDL, were significantly elevated in obese participants when compared to corresponding groups (0.82±0.23mmol/L) obese to (0.47±0.22 mmol /L) average weight at p<0.001 for VLDL, and (1.85±0.59mmol/L) obese to (1.09±0.51 mmol/L) average weight at p<0.001) for TG. There is also a significant difference in the fasting blood glucose among the groups. There was no significant difference among this study's other lipid fractions.

From the study findings, there is a progressive increase in the level of calculated remnant cholesterol among the groups, but it was not statistically significant, and there was an increase in the level of leptin among the groups. There was no significant correlation of leptin with remnant cholesterol in all the groups in the regression analysis. Hence, there was no significant positive association between leptin and remnant cholesterol; this can be explained in the context of a higher level of remnant cholesterol, which is not solely driven by adiposity and body mass index.