Introduction

For centuries, the world witnessed scarcity of food and people had low body mass index (BMI), but with industrial revolution, especially in developed countries, deficiency of food became a myth and people started gaining weight. In around the 19th century, overweight individuals outnumbered the underweight, but the scenario in developing countries was still the same, malnutrition was prevailing. By 2008, World Health Organization (WHO) estimated that more than 1.4 billion adults were overweight. These figures compelled researchers to find the causes and effects of obesity, the outcome of their extensive research was that, obesity was found to be multifactorial in origin, with delicate imbalance between genetic and environmental factors.

Obesity has become pandemic owing to an obesogenic environment. While research was mainly focused on understanding obesity and its path physiology, some new findings were observed that, not all individuals with obesity seemed to display metabolic abnormalities. Such individuals in the due course of time were named as healthy obese or metabolically healthy obese (MHO). These healthy individuals with obesity are characterized by high BMI or body fat with normal blood pressure (BP), lipid profile, and sugar levels [1]. Most of the studies have defined healthy individuals with obesity based on the above said parameters. However, far more studies have included proportion of visceral fat, less liver fat, 0 or less than 2 metabolic syndrome criteria based on National Cholesterol Education Program, Adult Treatment Panel III, and inflammatory profile. However, the fact is that, till date, no uniform definition has been framed. As per the Indian statistics, 13.3% of south Indians are MHO [2]. The proposed hypotheses for favorable health in obese yet healthy individuals, may be genetic, less visceral adipose tissue (VAT), ectopic fat deposition, healthy lifestyle, etc., however, detailed research in these phenotypes is needed to endorse these hypotheses.

Adiponectin is well characterized and studied with relevance to metabolic disorders associated with obesity. Many studies have shown high levels of adiponectin in healthy adults with obesity when compared to metabolically unhealthy persons with obesity.

C-reactive protein (CRP) is an acute phase protein. However, the lower limit of detection of CRP assays is about 2 mg/L. Hence, improvements were required, to detect lower levels, lower than 2 mg/L. Recent improvements in assay development have resulted in a new generation of high sensitive assay that can detect CRP at levels 100 folds lower than earlier.

Complement system constitutes many proinflammatory proteins. Among those, C3 is very important. It is critical for activation of the complement system. While C4 is the main protein of the classical pathway. C3 and C4 levels are considered as acute phase response protein assays.

Ceruloplasmin (Cp) is a member of inflammation-sensitive plasma proteins (ISPs) family that is used in clinical practice to measure the degree of inflammation. Its secretion and expression are high in obesity, and Cp found in adipose tissue is a major contributor to the circulating Cp level.

This study was done to look for the metabolic status in healthy individuals with and without obesity of different age groups and gender, which will help us in understanding the biochemical changes. We have investigated the levels of hormone adiponectin, the real adipocyte hormone, well characterized and studied with relevance to metabolic disorders associated with obesity. Secondly, we studied inflammatory markers as inflammation is the local protective response to tissue injury [3] along with systemic reactions known as acute phase response, this response is due to elevated levels of CRP, complement factors, Cp (acute phase proteins) [4], etc. CRP activates and modulates complement system. It binds to the first component of the complement cascade, and initiates the classical pathway, thereby increases local inflammation. It is also known that CRP inhibits the alternate and lectin pathways of complement through the recruitment of factor H. Thus, CRP plays a dual pro and anti-inflammatory role in its regulation of the complement system. Keeping in view obesity associated inflammation, caused by activated innate immunity responders, we consider innate immunity effectors as markers of inflammations like high sensitivity C-reactive protein (hs-CRP), C3, C4, and Cp. Thirdly, we studied oxidative stress markers, as inflammation and oxidative stress go hand in hand. It’s a vicious cycle, inflammation causes oxidative stress and vice versa. Adipose tissue is not an inert organ, and especially hyperplastic adipose tissue is active in releasing cytokines, which leads to consequences of the oxidative stress and damage to the lipid, proteins, and nucleic acids, leading to lipid, protein, and DNA peroxidation [5]. Common indicators of oxidative stress, particularly lipid peroxidation markers thiobarbituric acid reactive substances (TBARS) and total antioxidant capacity (TAC), even though nonspecific, are commonly used as indicators of lipid peroxidation and oxidative stress [6]. Previous studies have quoted that high BMI exerts increased oxidative stress.

Hence, we wanted to study levels of adiponectin and inflammatory markers like hs-CRP, C3, C4, and Cp, oxidative stress markers like TBARS and TAC in healthy adolescents (14–18) and young adults (19–25) with and without obesity of both the genders. The reason to choose this population was that, these individuals are firstly at increased risk of gaining weight due to physiological processes and at the same time have reduced physical activity as burdened by academics. Secondly, inflammatory process is still in the primitive state, as inflammation increases with aging. All these points were convincing for us to take up this study as to what happens as we age that is transition phase from adolescence to young adulthood in healthy males and females with and without obesity.

Methodology

This cross-sectional study was conducted in 16 schools and 23 pre-university colleges, belonging to 4 different quadrants of Belagavi city of north Karnataka in south India, Asia. Adolescents aged 14–18 and young adults aged 19–25 were selected as defined by WHO [12].

A pilot study was conducted on 5 healthy young adults and 5 adolescents with obesity, considering adiponectin as a main parameter and ensuring 5% error and 95% power of the test.

Details of sample size calculation:

n: sample size

Z: the number of standard deviations (SDs) an observation is from the mean for a set of data

S: SD

D: the expected difference between the means, divided by the expected SD

α: probability of making a Type I error, measure of the strength of the evidence that must be present in your sample before you will reject the null hypothesis and conclude that the effect is statistically significant

β: probability of making a Type II error (accepting the null hypothesis when the null hypothesis is false)

Adiponectin was estimated, and following results were derived:

SD of adiponectin in young adults = 2.0547 = S1

SD of adiponectin in adolescents = 2.987 = S2

Mean difference between young adults and adolescents = 1.1019

The following observations were put up in the formula:

$n={\left({\text{Z}}_{1-\alpha /2}+{\text{Z}}_{1-\beta }\right)}^2(2{\text{S}}_{\text{2}})/{\text{d}}^{\text{2}}$[13] 

Where Z_1-α/2 = 1.96[5% – LOS (Loss of significance)]

$$\begin{array}{l}{\text{Z}}_{1-\beta }=1.682\hfill \\ {\left(\text{S}\right)=(\text{S}}_{\text{1}}+{\text{S}}_2)/2=(2.0547+2.987)/2=5.041/2=2.5205\hfill \\ \text{d}=1.1019\hfill \\ n={\left(1.96+1.62\right)}^2\times 2{\left(2.5205\right)}^2/{\left(1.1019\right)}^2\hfill \\ ={\left(3.642\right)}^2\times 2{\left(2.52085\right)}^2/{\left(1.1019\right)}^2\hfill \\ =13.264164\times 12.709369/1.214183\hfill \\ =168.58/1.21\hfill \\ =139.32\hfill \\ n=140\hspace{0.17em}\text{in}\hspace{0.17em}\text{each}\hspace{0.17em}\text{group}\hfill \\ n=140+140=280\hfill \\ n=280\hfill \end{array}$$

Accordingly, a final sample size of 280 was calculated, of which 140 adolescents and 140 young adults were enrolled. Sampling technique: cluster sampling technique was used, according to Belagavi district report, there are 46 private schools and 31 pre-university colleges in urban Belagavi city. Belagavi area was divided into 4 quadrants and from each quadrant schools and pre-university colleges were selected proportionately. Of these, only 16 schools and 23 pre-university college deans gave permission for data collection.

Study protocol: once the ethical committee (JNMC Institutional Ethics Committee on Human Subjects Research) clearance was obtained (Ref No: KLEU/D 6596-6599; date: June 29, 2010) then, permission was obtained from the selected heads of the institution prior to examining the students of schools and pre-university colleges.

Adolescents: school health records were accessed to look for height, weight, then BMI was calculated, and students with and without obesity were identified.

Young adults: while in colleges, most of the participants were aware about their BMI, hence individuals approximately in the range of normal and obese BMI were identified (n = 326) and further screened (details mentioned in Figure 1).

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Figure 1. 

Participant information

Identified participants were explained about the study in detail and requested to fill in the written consent form if aged more than 18 and assent from the participants with consent of the parent or the guardian if aged less than 18. A total of 300 individuals were enrolled, of which 145 were adolescents and 155 were young adults. Details of the enrollment, inclusion, and exclusion of the participant are given as in Figure 1.

Materials and methods

Results

Two hundred and eighty individuals aged 14–25 years meeting the eligibility criteria were enrolled in the study. Of these 280, 140 were adolescents and the rest 140 were young adults. Further, equal number of non-obese and obese were enrolled. Details of study participants are provided in Table 1.

Impact of age on adiponectin: adiponectin levels were low with increase in age, in participants of both categories, non-obese (P = 0.01) and obese (P = 0.01, Table 2).

Impact of age on inflammatory markers: hs-CRP levels were high with increasing age in both categories, non-obese (P = 0.04) and obese (P = 0.01, Table 1). C3 and C4 levels did not vary with age in participants with obesity (C3: P = 0.51, C4: P = 0.681), while C3 levels were higher with increasing age, in participants with obesity (C3: P = 0.001, whereas C4 did not change: P = 0.38). Cp levels were higher with increasing age, in participants without obesity (P = 0.01) and participants with obesity (P = 0.01, Table 2).

Impact of age on oxidative stress markers: there was no significant difference in the levels of TBARS (P = 0.289) and TAC (P = 1.0), with increasing age in the non-obese. While in the obese, TBARS (P = 0.01) levels were higher and TAC (P = 0.01) levels were low (Table 2).

Impact of gender on adiponectin levels: there was no difference in adiponectin levels amongst non-obese females and males (P = 0.308), while obese females had lower levels than males (P = 0.01, Table 3).

Impact of gender on inflammatory markers: there was no significant difference in the levels of hs-CRP among females and males belonging to non-obese and obese categories [non-obese (P = 0.628), obese (P value = 0.913)]. Whereas there were significantly higher levels of C3 in females, than males in both non-obese and obese categories [non-obese (P value = 0.01), obese (P value = 0.01)]. No change was observed in the levels of C4 amongst non-obese females and males (P = 0.08), while it was higher in obese females than males (P = 0.01, Table 4). Levels of C3 and C4 were higher in females than in males, except for hs-CRP & Cp.

Discussion

With increase in age, adiponectin levels were low in healthy individuals with and without obesity. Our results are in line with a study conducted by Vilarrasa et al. [25] in 2005, while most of the studies [26–28] were contrary to our findings as no changes in levels of adiponectin with age were documented [29]. With aging, percent fat mass increases in terms of VAT, hence decline in adiponectin levels is a physiological process. Also, age-related decline in testosterone and estrogen levels has been shown to inhibit adiponectin production [30].

In our study, there was a notable trend of high CRP values with increasing age (adolescents have lower values than young adults) in non-obese and obese categories. The same results have been documented previously [31, 32]. Inflammatory changes are a common phenomenon of aging.

Age had no impact on the levels of C3 and C4 in persons without obesity, as the levels in adolescents and young adults did not vary. However, in persons with obesity, C3 levels were higher in young adults when compared to adolescents. With aging adiposity increases, consequence of which is increased expression of complement factors, especially when aging is associated with obesity. According to our knowledge, there were no studies documented that could support or contradict our results in relation to C3 and C4.

Cp levels were in higher range in healthy young adults than adolescents, among obese participants. Previous studies have shown that Cp increases with age [33]. However, these studies have been done in adults without adolescents into consideration.

Among participants without obesity, as age increased, TBARS levels were higher and TAC levels were lower. Age-related oxidative stress has been documented previously [34, 35] while a study contradicted our results where higher levels of TAC were observed with aging [36].

Previous studies [37, 38] have convincingly shown that females have significantly higher levels of adiponectin than males. We, too, have documented similar trend in healthy males and females without obesity. However, statistical significance could not be achieved. In males, testosterone selectively reduces adiponectin formation by inhibiting its secretion from adipocytes [39], thereby extending sexual dimorphism to adipose tissue. In our study, females exhibited significantly lower adiponectin compared to males. No studies support our finding. However, higher level of adiponectin in western female population was documented [40–42]. Notably, women in our study had a higher WHR which could be more associated with obesity-related complications leading to low levels of anti-inflammatory, anti-diabetic hormone adiponectin.

In our study, there was no gender difference in hs-CRP levels. Previous studies have shown that women have higher hs-CRP levels than men [43–45]. The quantity and distribution of body fat appear to influence the hs-CRP levels to a greater extent in women than men [46].

In our study, gender had no impact on Cp levels. Previous studies have shown that Cp concentrations are higher in females [47].

From the above discussion, commendable points are that there is a statistically significant link between adiponectin, inflammation, and oxidative stress. In healthy adolescents with obesity, adiponectin levels were low, while inflammatory markers C3, C4, and Cp levels were high when compared to individuals without obesity. The inflammatory marker levels were high and adiponectin and TAC levels were low in young adults.

Reduced levels of anti-inflammatory adipokines, adiponectin, and increase in inflammatory markers, the so classified “healthy obese” are at risk of inflammation or progressing towards metabolically unhealthy obesity, as they progress from adolescent age group to young adulthood [48]. This phase of transition is crucial, hence dietary & lifestyle modifications at this junction may help the individuals to stay healthy.

Furthermore, with the discussion, it looks like participants with obesity may be having higher visceral adiposity and visceral adipocytes tend to be smaller than subcutaneous adipocytes but have greater potential to secrete cytokines [49]. Hence, we had to find the correlation between adipocytokines and obesity.

These points clearly show that transition from adolescence to adulthood leads to increase in visceral adiposity, causing inflammatory and oxidative stress changes in the adipose tissue, particularly in females even though there was higher physical activity status. This transition from adolescence to adulthood is a crucial transition phase in life of human beings. Lower levels of adiponectin, TAC, and higher levels of C3, predicted that participants with obesity are at a state of inflammatory and oxidative stress changes, though they could be at a subclinical state. Hence, participants with obesity, though found to be non-diabetic and non-hypertensive, had to be cautiously screened and treated. Screening of adolescents with obesity, with WHR would predict visceral fat better than just BMI. Decrease in adiponectin and TAC and increase in inflammation emphasizes that adiponectin may have a protective function which prevents the establishment of co-morbidities associated with obesity at an early age of adolescence and young adulthood. Intervention has to be planned considering anti-oxidants in the treatment regime, as treatment with antioxidants could also restore the regulation of adipokines like adiponectin [50]. Improving the expression of adiponectin with its receptor can prove to be useful in the treatment of obesity and obesity related diseases [51].