Heavy Metals Concentrations in Some Roadsides with Different Traffic Volumes in Rasht City-Iran

Heavy Metals Concentrations in Some Roadsides with Different Traffic Volumes in Rasht City-Iran by Ebrahim Alinia-Ahandani* in Open Access Journal of Biogeneric Science and Research

Abstract

Concerns around the usage of motor vehicle emissions on human health issues are especially concentrated on aerial pollution and are regulated via controls on tailpipe emissions. Toxic heavy metals are mentioned as a variety of important environmental contaminants cause of their none-degraded or none-destroyed properties. In this study, we investigated the pollution of heavy metal of pointed locations in the roadside dust in Rasht province (center of Guilan province in Iran northern). In this study, we have tried to considerate to road dust aspects in roadside soils of two distinct points: along road with dense traffic (20 street, high traffic volume) and road with lower traffic, a local road (20 street, low traffic volume). Samples of road dust (20 in general) were gathered under stable weather conditions during June and July of 2020. Samples of road dust were collected and analyzed for their variety of lead (Pb), Zinc (Zn), Nickel (Ni), Cobalt (Co) and Cadmium (Cd) concentrations by ICP-OES. The results have demonstrated that all heavy metal amounts except Cd, are higher than acceptable values in the target soils. Tend to illnesses, especially carcinogenic
effects affected by these toxic metals are predictable.

Keywords: Heavy metals; Roadside; Rasht, Toxic; Health.

Introduction

Changing the life style and using the machinery gadgets are being varied daily. The main value of the heavy metals are toxic to the living organism and even those considered as essential could be toxic if present in excess. The heavy metals can follow significant biochemical process posing a threat to human health, plant growth and animal life. [1-7]. Accumulation of metals in soil could affect the ecosystem safety and pose a threat to animals, plants, and human. High concentrations of metals in the plant could inhibit the ability of the plant to produce chlorophyll, increase the plant oxidative stress and weaken stomata resistance. Roads, plastics, industrial effluents, and sewage have polluted and occurred many issues for vegetation, animals, and humans [8-25]. One of the most pointed chemical contaminants is heavy metals, causing irreparable damage [26]. Human activity increases the level of heavy metals pollution in the nature [27]. Because these compounds are not metabolized in the body, they could be stored in body tissues such as muscles and bones. Heavy metals have the potential to cause illnesses such as mental retardation, hearing impairment, immune system dysfunction, brain diseases, blindness, muscle weakness, and cancer [28,29]. Roads are usually rich in Pb, Zn and copper [30-32].

The pollution of soils by heavy metals from automobile source is a serious worldwide environmental issue. These metals are released during different operations of the road transport such as combustion, component wear, fluid leakage and corrosion of metals. Lead, cadmium, copper and zinc are the major metal pollutants of the roadside environments and are released from burning of fuel, wearing out of tyres, leakage of oils, and corrosion of batteries and metallic parts such as radiators etc. The presence of these metals on the road is usually due to leaded gasoline, tire wear, corrosion of roadside safety fences, and wear of brake linings [33,34]. Also, the source of Ni and chromium in road dust is probably due to corrosion of vehicular parts. Moreover, heavy metals can enter the environment through natural paths, such as mineral erosion, wind, river, groundwater, and volcanic activities where all the items are connected each other. Malkoc (2010) did the research on the levels of heavy metal pollution in roadside soils of Eskisehir, Turkey. Fifteen soil samples were taken from three different lines: only - tramway lines, only - traffic lines, and both traffic and tramway lines and analysed for different heavy metals viz., Cd, Cu, Cr, Fe, Hg, Mn, Ni, Pb, and Zn. The level of pollution in soil was estimated based on the geoaccumulation index (Igeo), enrichment factor (EF), pollution index and integrated pollution index (IPI). The values of the integrated pollution index (IPI) were found to be in the order of Pb > Zn > Cu > Fe > Mn > Ni > Cr > Cd [34-40]. In this research, the concentrations of heavy metals such as lead ( Pb ), Zinc (Zn), Nickle (Ni), Cobalt (Co), and Cadmium (Cd) in road in Rasht province areas (Iran northern) were studied using inductively coupled plasma atomic emission spectroscopy (ICP-OES).

Experimental

Study Area

Rasht city center was the place for selecting the samples. All samples were randomly selected from several points, where mainly the vehicles running on these roads use gasoline and diesel engines which were or target. A mass of people traveling daily on these roads are subjected to its dusty environment to introduce as a point.

Measurements and Characterization

A PerkinElmer (Shelton, CT, USA) Optima 3300 DV ICP-OES instrument was used for determinations.

Preparation of Samples

Totally, we have tried prepare samples according to routine methods which were used in literatures. At each of these points, dust samples were collected within 0.5 m distance from the edge of the pavement. These surface soil samples were taken from the top (0-2) cm of soil. At each sampling point, three sub-samples were taken and then mixed to achieve a bulk sample. Such a sampling strategy was adopted in order to decrease the possibility of random effect of urban waste not obviously visible. Samples were placed in plastic bags, labeled by attention, and taken to the laboratories for further processes. Soil samples were digested with HCl, NHO3, and H2O2 according to U. S. EPA 3050B method and prepared for results [35-39].

Results and Discussion

The results of heavy metals from the samples are given in (Tables 1 & 2). The results have shown that all heavy metal amounts except Cd, are higher than reasonable values in natural soils which were investigated. The average concentration of Pb was 822.1 mg/kg. Pb is remarkably affected by car exhaust and vehicle emissions, eg tire wear, bearing wear. This high concentration of lead mostly is due to the non-standard gasoline applications. The average concentration of Zn was 712.2 mg/kg, which is due to the application of Zn compounds as antioxidants and as detergent/dispersants improving agents for motor oil in the car and machinery industries. We express that the source of Ni in street dust is cause of the corrosion of vehicular parts or related industries. The high rate of corrosion and wear from old vehicles (due to the use of worn-out cars in Iran) plying these roads could have accounted for the significant levels of anthropogenic contributions of Ni in the road dust. The average street concentration of Co was 32.20 mg / kg, which was reasonable value.

Table 1: Mean concentration of metals (mg/kg) in street dust (dense traffic).

Table 2: Mean concentration of metals (mg/kg) in street dust (lower traffic).

The mean Cd concentration has been measured in the street 2.06 mg/kg. Cd is a relatively rare heavy metal, which occurs naturally in combination with other metals. Cd has been observed in road dust due to its presence in both automobile fuel and in soil. Prolonged exposure to Cd could affect some related organs with the kidney being the principal target where it is being researched as more in literatures every day. Because of the special climatic condition of Rasht, which is significantly rainy in the year, there is a concern that these toxic heavy metals will enter the surface water or groundwater which are usable in different applications and have daily usages. In northern Iran, natural products and farm harvestings are also irrigated from surface and groundwater, increasing the concerns that these metals may enter the food chain or play some dependable roles in the health tips of the people in this area [40-42].

Conclusion

Generally, the average concentration of some heavy metals in roadside soils of Rasht province area (northern Iran) was measured and compared by attention. The results have showed that the amounts of studied heavy metals are high in some areas and threaten the health of all organisms especially the neighbourhoods. Cause of the rapidly increasing population of Rasht city, the pollution rate along this roads is expected to increase in the coming years. Some protective measures such as the use of public transportation, conversion of liquid fossil fuel to gaseous fuel or other clean energies, having more green landscapes as well as storing the natural sources and assessing the pollution centers to control and better managements are suggested to combat this problem.

More information regarding this Article visit: OAJBGSR

https://biogenericpublishers.com/pdf/JBGSR.MS.ID.00169.pdf

https://biogenericpublishers.com/jbgsr-ms-id-00169-text/

Hepatocellular Carcinoma and Recurrence Rate: Comparison of Living and Deceased Liver Donor Transplantation

Hepatocellular Carcinoma and Recurrence Rate: Comparison of Living and Deceased Liver Donor Transplantation by Michele Finotti in Open Access Journal of Biogeneric Science and Research

Introduction

Hepatocellular carcinoma (HCC) represents the 75-85% of primary liver tumors. Chronic liver disease, in particular cirrhosis, is the leading risk factor for HCC [1]. Liver Transplantation (LT) is an effective therapy for HCC, allowing an oncological resection of the tumor and a resolution of the underlying liver dysfunction. However, due to the shortage of liver grafts and a concomitant increase of candidates for LT, a longer waiting time for LT is occurring [2]. In patients affected by HCC, a longer waitlist is associated with a higher risk of drop out, especially due to tumor progression. In the last years, Living Donor Liver Transplantation (LDLT) has been evaluated as a viable option to Deceased Donor Liver Transplantation (DDLT) to reduce waitlist mortality and/or the risk of patient drop out.

With the increased experience in LDLT for patients with HCC, concerns have been raised about the outcome in terms of HCC recurrence and Overall Survival (OS) compared to DDLT. The aim of this paper is to summarize the available studies comparing DDLT versus LDLT in patients affected by HCC, especially in terms of HCC recurrence rate.

HCC Recurrence after LDLT

The correct patient selection and prioritization for LT are ongoing matters of debate in DDLT. Variables such as number, dimension and bio markers of HCC, especially AFP, have been proposed to select the patients with lower risk of HCC recurrence and the best OS after LT. The Milan criteria (a single tumor size of ≤5 cm or up to 3 tumors with sizes ≤3 cm in diameter with no macrovascular invasion) are widely apply to select HCC patients for LT [3-6]. However, different selection criteria have been proposed, such as utility models (based on radiologic morphology) biology models, or a combination of the two [7]. HCC recurrence is an essential variable also in the LDLT, and a debate has been raised about the HCC recurrence after LDLT compared to DDLT.

Some studies showed that LDLT was associated with a higher HCC recurrence rate, compared to DDLT [8-11]. Some features related to the LDLT procedure have been proposed as possible explanations.

In the LDLT the graft used is different compared to DDLT. The whole organ is usually used in the DDLT, while the right liver graft is mainly used in adult LDLT. Some studies suggested that the consequent liver regeneration after LDLT, with a rapid increase in growth factors and cytokines, might stimulate HCC recurrence. Furthermore, the small-for-size grafts have been associated with higher endothelial growth-factor expression and angiogenesis [12-16].

However, the implication of these factors in HCC recurrence is questioned [17]. A technical aspect has been suggested as possible further explanation of higher HCC recurrence in LDLT showed in some studies. In particular, in the recipient, the preservation of the native inferior vena cava, the longer hepatic artery and bile duct might be associated with insufficient tumor removal and HCC residue and dissemination.

Another variable introduced with the LDLT compared to DDLT is the waiting time list. In the LDLT the waiting time list is drastically reduced, with the potential to overcome the organ shortage, reducing the waitlist mortality and the risk of drop out due to HCC progression. For example, Bhangui et al. reported the waiting time for LDLT patients (2.8±2.4 months) was significantly shorter than DDLT (7.9±9 months; P<0.001), and some center reported a median of 44 days [18,19].

However, time in the waiting list is another important indirect selection criterion that can influence the HCC recurrence. During the waiting time, the patient is usually observed and, in some cases, treated with loco regional treatments, such as TACE or ablative techniques (MWA or RFA). The waitlist and the response to the loco regional treatments could show the patient with a more aggressive HCC pattern. In the LDLT this “test of time” is significantly reduced compared to DDLT, and the results of the higher HCC recurrence can be the consequence of the inclusion of patient with aggressive tumor [8, 10, 11, 20-24].

Last but not least, patients who underwent LDLT often exceeded the most common HCC inclusion criteria (Milan criteria, UCSF) and the criteria used for DDLT are not the same for LLDT. Most studies report an LDLT offered to a patient affected with a more advanced HCC, raising concern about the ethical aspect [25]. All these factors would predispose the LDLT to have a worse outcome in terms of OS, RFS and HCC recurrence. However, as previously reported, the data are inconsistent.

To date, few meta analysis comparing the HCC outcome after LDLT or DDLT are available. In 2012, Lian et al. evaluated 1310 patient affected by HCC underwent to LDLT or DDLT in seven studies. Six were retrospective cohort studies, one was a prospective study, none was randomized trial [20]. To note, the tumor-related baseline variables, such as the TNM stage, size, and number of tumors, tumor differentiation, microvascular invasion, MELD score, Child-Pugh class, percentage of patients beyond the Milan or UCSF criteria, and treatment before LT were comparable between groups in all studies. In the LDLT groups, a significantly shorter waiting period and cold ischemia time have been showed. At 1, 3 and 5 years the LDLT and DDLT recipients had similar OS rate with no significant heterogeneity among the studies, except for the 5-year survival rates (4 studies showed a statistically significant heterogeneity; P . 0.13, I2 . 47%). Similarly, the RFS at 1,3 and 5 years was similar between LDLT and DDLT with no significant heterogeneity among the studies. The HCC recurrence rate at 1,3 and 5 years showed a similar pattern, but varying degrees of heterogeneity were found in the studies comparisons at 1,3 and 5 years20.

An additional analysis was performed comparing LDLT and DDLT in patients with HCC Milan criteria in or out. At 1,3 and 5 year the OS and RFS were similar between the two groups within the Milan criteria, while the LDLT recipients had a greater 1-year recurrence rate than DDLT recipients (insufficient data were available to perform a 3- and 5-years comparison). In the patients beyond Milan criteria, the OR, RFS and recurrence rate were similar between DDLT and LDLT20.

In 2019, Zhang et al. published a meta-analysis selecting, with strict inclusion criteria, seven studies, reporting a significantly increased risk of HCC recurrence in the LDLT group compared to DDLT group (P = 0.01) [26]. Zhu et al. performed a meta-analysis comparing LDLT and DDLT in twenty-nine studies with 5376 HCC patients with an Intention to Treat analysis (ITT). At 1,3 and 5 year the OS, DFS and HCC recurrence were similar between the LDLT and DDLT groups. Furthermore, LDLT was associated with better 5-year intention-to-treat patient survival than DDLT (RR = 1.11, 95% CI = 1.01–1.22, P = 0.04) [27].

The inconsistent data reported by the previous meta-analyses can be explained by some bias associated with the studies. These meta analyses compared multiple studies that often have an extremely heterogeneous transplanted population. HCC staging system, selection criteria, pre-LT treatment, waitlist time, donor preservation, surgical technique, and post LT management are some of the most variables that contribute to increase the complexity of LDLT evaluation. Furthermore, the evaluation of the outcome starting not at the time of the LT but at the waitlist (ITT analyses) is another factor leading to different results among the studies.

Conclusion

Deeping in the studies that reported a higher HCC recurrence rate in LDLT compared to DDLT, most of them reported patients with higher levels of AFP, more tumors beyond Milan and/or UCSF criteria and micro vascular invasion. Furthermore, less pre-LT ablation therapy is used in patients treated with LDLT due to the shorter waiting time compared to DDLT. Thereby, the main reasons for a different outcome reported by some studies and higher HCC recurrence in LDLT compared to DDLT could not be related to the type of technique per se (LDLT or DDLT), but probably to the different patient’s selection.

Transplant benefit might be the correct way to evaluate the real outcome of LDLT compared to DDLT. Most of the studies evaluated only the post LT outcomes, without including the results for patients on the waitlist. In particular, a percentage of patients listed for DDLT will drop out from the waitlist due to tumor progression, while in the LDLT group with a shorter waiting time allows these patients with more aggressive HCC pattern to be transplanted, affecting the final outcome. With this consideration, probably the transplant survival benefit in the LDLT is not correctly evaluated compared to DDLT [20]. In the last years, studies with an ITT analysis (evaluating the outcome from the time of listing, and not from the time of LT), showed comparable results in terms of OS and HCC recurrence among LDLT and DDLT groups [28]. In particular, Goldaracena et al. showed a transplant benefit of LDLT compared to DDLT in an ITT analysis associated with a reduction in the drop out rate in the LDLT groups. Similar results were obtained by Wong et al. that performed a ITT and propensity score matching analysis of 375 patients with 5-year OS of 81.4% for LDLT versus 40.8% for DDLT.

In conclusion, LDLT was firstly associated with a higher HCC recurrence. In the last years, most studies showed similar results comparing LDLT to DDLT in terms of HCC recurrence and OS, especially at ITT analysis. To date, no randomized studies are available comparing LDLT to DDLT. The different outcome between LDLT and DDLT might be related more to the variables associate with the procedure (patient selection, HCC staging, waitlist, pre- and post-LT treatment) than the procedure itself.

More information regarding this Article visit: OAJBGSR

https://biogenericpublishers.com/pdf/JBGSR.MS.ID.00168.pdf

https://biogenericpublishers.com/jbgsr-ms-id-00168-text/

Food Security, Food Desert and Common Sense Solutions

Food Security, Food Desert and Common Sense Solutions by Terrence W Thomas* in Open Access Journal of Biogeneric Science and Research

Abstract

The commonly accepted definitions of food desert and food insecurity shape most efforts to address the adverse effects of both phenomena. The primary features of food deserts are places where low-income people reside, communities that are more than a mile from a full service supermarket and reduced access to sources of fresh fruits and vegetables. On the other hand, food insecurity is a condition where people do not have enough nutritious food to meet recommended daily requirements. In some instances, food security definitions stipulate that the food available should be culturally acceptable. Thus, peculiar features of the individuals, the place and type of food available or eaten inform our understanding of the twin concepts of food deserts and food insecurity and drive our efforts to address them. * start here with cs definition and relevance

Solutions such as improving access to fresh fruits and vegetables, providing nutritious foods through various support programs such as SNAP and food stamps, projects that fund development of grocery stores in underserved communities, promotion of local community-based food production and nutrition education programs are based on the forgoing definitions. These efforts are intuitively appealing common-sense solutions because they appear logical and reasonable. That is, to an average reasonable person these efforts seem very appropriate and with a great likelihood of solving the problem. Widely received knowledge and practice ground these common-sense solutions. Yet, progress in solving the nutrition related problems associated with food desert and food insecurity is much slower than anticipated, or to take a more conservative outlook, the problems seem intractable. We are often bewildered that proposed solutions that seem so obvious and logical fail to drive progress forward at a rate that would allow us to envision the disappearance of the problem in the near future.

*One possible explanation for the slow progress in resolving the problems associated with food deserts and food insecurity is our reliance on common sense knowledge as the foundation for building solutions. In many instances, common sense knowledge may not be enough to fuel our quest for solutions that produce great impact. The reason for this is common sense knowledge does not give us access to deeper insights that play a vital role in solving the problem. For the purpose of this discussion, common sense, as Watts [1] described it, is the knowledge, insights and experiences individuals obtain overtime as they interact with and deal with everyday situations and people. From this perspective, common sense could include knowledge that lie in the realm of professions and professional practice. Because common sense knowledge is intuitive -- readily available to us, knowledge we can draw on and have the expertise to apply; it is our go to everyday resource and available reserves for making sense of reality without rigorous study and review. It serves us well when applied to simple everyday situations (proximate reality). From the author’s perspective, the core feature of common-sense knowledge is the way in which we appropriate and use it. For instance, we take certain theoretical knowledge or knowledge derived from practice as given. Thus, in applying it without deep examination of its weakness or relevance to the situation, the well-accepted knowledge is more like a tradition; because its use is justified not on its merits relative to the situation at hand but by its time-honored acceptability, reputation, and ease of access or availability.

However, in many complex situations such as food deserts and conditions such as food insecurity, a multitude of factors potentially influence the behavior of individuals or the choices they make. In such instances, there is far more information available to the actor than may be necessary for making a decision at any particular moment (satisficing). The actor uses his common-sense knowledge of the situation to determine the information relevant to the action he proposes to take. The observer of behavior also faces a similar situation, one that is also replete with information. In this situation, however, the observer cannot know for sure what pieces of information is relevant, that is, what information the actor actually used in making his decision. He too relies on his common-sense knowledge to surmise the relevant information. Alternatively, he may ask the actor to tell him about the information he used. The problem here is twofold. First, although the actor is more conversant with the relevant pieces of knowledge than the observer is, still he may not be able to articulate at any instance all the knowledge he acted on. Second, the observer may use his common-sense knowledge to figure out the relevant information used to drive decision or behavior. However, given the vast quantities of information available to the actor in any decision-making context, it is difficult for the observer to know which piece of information is relevant (the information actually used) to the decision situation of the actor.

Additionally, certain relevant information may not be accessible to analysis via or common-sense driven models. For example, potential interaction among one or more factors or features of the situation. That is, it is not possible to account for the results we observe in terms of the properties of individual features of the situation or the individual; the whole is greater than the sum of its parts and qualitatively different from the separate parts. Just as it is impossible to account for the overall function of the brain by studying individual neurons in exhaustive detail. Nor is it possible to assess the nutritional status of food desert residents by studying separately and in detail the carbohydrate content of his breakfast or just his breakfast. In the same way, the observer cannot possibly account for behavior just in terms of the features of the individual and his situation. Nutritional status and eating habits are emergent phenomena of complex socio-economic and physical systems; they are the manifestation of many interacting features of individuals and the overall environment. Thus, our ability to access all the information that may be relevant to any situation is difficult or may be impossible using current methods –surveys, focus groups, listening sessions or even experiments as standalone approaches.

The fact is questions regarding the choices we make and why we make them and our efforts to influence people through various means to make different choices dominate social science discourse1. Moreover, we build our models of reality on the foundation of preferences, incentives, opportunities and motivation related to the features of the individuals and their environment. We derive our common-sense knowledge and intuition from these models. However, although these models bring clarity and order to our thinking, they do not fully represent the reality we deal with and may not be able to do so. Our models do not sufficiently account for the frame problem—identifying all the relevant features from among the multitude of features in a situation. Nor do they account for the micro macro problem that emergence represents1. In this light, our common-sense knowledge suffers from server blind spots that lead to errors when we rely on common sense judgement to deal with novel and complex situations outside of our own behavior and circumstances.

Therefore, relying too much on applying common sense to understand and find solutions to common but complex problems such as anticipating or managing the behavior of large number of people is fraught with errors. In these situations, many relevant features lie beyond our conscious cognition. Additionally, of the several features that may be within reach of our senses, it may be impossible to tell which is relevant to the situation based on common sense judgement alone. For example, our research project conducted in a food desert, community leaders fervently believed that providing a grocery store in the food desert neighborhood in Eastern Greensboro would flourish because of the high level of patronage it would receive from community members who would now have access to essential and high-demand grocery supplies. However, the cooperative grocery store, Renaissance Coop Grocery Store, closed within a year of opening for lack of patronage. Obviously, the usual market research and feasibility study failed to foresee this outcome. It remains an open question why low-income people who live in a food desert failed to support the Coop Grocery Store. After all, the Coop provided access to fresh and vegetables, other essential food items, and household items not available to them in the community prior to the establishment of the Coop Grocery Store. In addition, many of them are members of the Coop. Even without market research data, it seemed clear from common sense reasoning that it would be in the interest of residents to support the Coop but they did not. One thing is certain, the decision model employed to justify establishing the Coop ignored relevant factors that were determinants of success or it failed to recognize them because they existed outside the theory and logic of the model.

Another example of the application of common-sense reasoning was the decision to use Coop Grocery Store issued gift cards as incentive for participating in nutrition education workshops instead of gift cards issued by the State Employees Credit Union. Even though both gift cards had similar features and carried the same face value, workshop participants preferred the credit union issued cards. In the eyes of the participants, the credit union issued cards were more valuable because participants could use these cards anywhere to purchase goods and services, where as participants could only use the Coop Grocery Store issued gift cards at the Coop. The decision to use Coop issued gift cards resulted in a fall in attendance because these cards lost some of their incentive value. The decision to use Coop issued gift cards seemed reasonable because it encouraged participants to support the Coop but it had an unanticipated negative impact on participation in the nutrition education workshops. This is a classic example of common-sense reasoning. It is the type of reasoning we apply in our attempt to solve a problem based on knowledge of a simple aspect of the problem or incomplete understanding of a situation rather than the complex connection of the problem or situation to many other things.

The fact is low income people by definition have a very small income so the value of, say, an incentive to them increases as the options available to them for spending it increases. So, in order to get the maximum impact from the incentive, participants should receive gift cards they can spend anywhere. This latter approach to reasoning is counter intuitive given the context of the decision-making---the immediate goal is to increase patronage for the Coop Grocery Store. Community leaders see the gift cards paid to participants as an easy way to do this, and at the same time, participants would be supporting a venture in which they are part owners. These are obvious, logical, easily accessible and valid reasons for giving participants Coop issued gift cards. However, providing gift cards with options to use them anywhere would increase their incentive value to the participants and boost attendance at workshops, but this line of reasoning was outside of the prevailing common-sense model.

Watts cited the difference in organ donation rates between Austria and Germany due to the default opt out policy prevailing in Austria and absent in Germany, as an example of an explanation that eludes the traditional social science model. Differences between both countries based on easily accessible information about costs and benefits, incentives, preferences and attributes would not have explained the difference in donation rates between both countries. In applying our models, we forget their inherent fallibility and proceed to apply them as if they were perfect representations of the realty we seek to address. We fail to acknowledge or leave room for the emergent solutions; we do not deliberately look for opportunities to learn from the feedback generated by the portion of reality outside the model as we conduct a study or implement a project.

Social systems represent the archetypal complex system. The nonlinear interactions among inter dependent components and individuals amplify small random oscillations to produce unpredictable outcomes, making it difficult for stable patterns to become manifest. A useful way to look at complexity is in terms of the amount of the observable variations we are able to explain. For example, in a complex social system, models only capture a small portion of the variation we observe; our models are simple relative to the system variation it is attempting to capture. Whereas a system is simple, as in physical systems, because complex models are able to capture most or all of the variation we observe. Given the unpredictability of complex social systems, and the fact that models capture only a small part of the variation, there is a lot that we do not understand. Therefore, we should avail ourselves of the opportunity to learn as we carryout research and development projects. This means instead of looking for definitive answers we should be prepared to engage those whose behavior and circumstances we are attempting to study and improve by co-creating, designing, prototyping, experimenting, testing and refining solutions in an iterative process in order to maximize learning opportunities. Because in complex systems problems do not remain solved, given the emergent properties of these systems, the types of projects that purport to seek and develop a definitive scalable solution is antithetical to the reality of complex social systems.

More information regarding this Article visit: OAJBGSR

https://biogenericpublishers.com/pdf/JBGSR.MS.ID.00167.pdf

https://biogenericpublishers.com/jbgsr-ms-id-00167-text/

Handgrip Strength and Vertical Jump and their Relationship with Body Fat in Hong Kong Chinese Children and Adolescents by Clare Chung-Wah Yu* in Open Access Journal of Biogeneric Science and Research

Handgrip Strength and Vertical Jump and their Relationship with Body Fat in Hong Kong Chinese Children and Adolescents by Clare Chung-Wah Yu* in Open Access Journal of Biogeneric Science and Research

Abstract

Aim: To examine the associations of handgrip strength and vertical jump with gender, pubertal status and body composition, and establish normal reference values of handgrip strength and vertical jump of Hong Kong Chinese children and adolescents.
Methods: This study included 1154 children and adolescents aged between 8 and 17 years, who participated in a territory-wide cohort study. Data of anthropometry, pubertal status handgrip strength and vertical jump were collected. Percentile curves of handgrip strength and vertical jump were constructed using the LMS method. General linear model was used to evaluate the effects of age, sex, pubertal stage, body size, body fat and the possible 2-way interactions on handgrip strength and vertical jump.
Results: According to the international BMI cutoffs, the prevalence rate of overweight or obesity (20.7%) in our cohort of children was similar to that obtained from previous local report. General linear model revealed that handgrip strength and vertical jump increased with increasing age, and boys were significantly stronger than girls after aged 12 year or older. Among overweight/ obese children, those with high body fat had significantly lower handgrip strength than those with low body fat. A full model
including age, sex, BMI z score, body fat z score and age*sex interaction explained 67.8% and 60.1% of the variance of handgrip strength and vertical jump respectively. Handgrip strength and vertical jump was positively associated with age, male sex and BMI z score, but was negatively associated with body fat z score.
Conclusions: Classifying children’s weight status by BMI cutoffs, additional information on children’s body composition should also be considered. Reference values for handgrip strength and vertical jump are established for Hong Kong Chinese children and adolescents aged 8 to 17 years.

Keywords: Bioelectrical impedance; normative fitness values; body fatness, muscular strength.

Introduction

Childhood obesity is the most serious global public health challenges of the 21st century [1]. It is reaching alarming proportions in many countries, in just 40 years the number of schoolchildren with obesity has risen more than 10-fold, from 11 million to 124 million [2]. Hong Kong, as one of the most urbanized cities in China, cannot escape from this global epidemic and the overweight prevalence in Hong Kong children was 20.4% [3]. Childhood obesity undermines the physical, social and psychological well-being of children [4,5]. One of the most possible explanations for this global epidemic consists in the decline of fitness, produced primarily by decreases in physical fitness [6]. Obesity and physical fitness are two interrelated factors and changes in one may cause changes in the other [7]. A recent longitudinal study confirmed a strong reciprocal relationship between physical fitness and obesity in Hong Kong children [8].

Muscular strength, as an important component of physical fitness, has been increasingly recognized in the pathogenesis and prevention of disease [9,10]. Some evidence suggests that muscular strength is inversely and independently associated with cardiovascular and all-cause mortality events in both healthy adults and clinical populations [9,11]. Muscular strength is also inversely associated with age-related weight gain, risk of hypertension and prevalence of metabolic syndrome [9,12,13]. Similar associations have also been reported in children [14-16]. This phenomenon may be partly explained by the fact that muscle tissue is an important organ influencing metabolism and can directly affect risk of metabolic diseases [17]. However, muscular strength changes with growth, and therefore, age-specific values obtained in healthy children should serve as a reference for with acute and chronic conditions using muscle strength for diagnostic purposes, follow-up, or to assess the efficacy of therapy [18]. For population-based studies, it is essential that the techniques involved should be simple and quick, so that such studies do not have follow laboratory conditions strictly. Two tests which satisfy these conditions are the handgrip and the vertical jump.

The vertical jump, a measure of lower body power, and handgrip strength, a measure of upper-limbs muscular strength, have both been acknowledged as being strong measures of one’s health, and recommended for potential use in school fitness testing which in line with recent recommendations [19]. Moreover, handgrip strength can be used as a tool to have a rapid indication of someone’s general muscle strength [20]. Meanwhile, the vertical jump is a simple method to calculate peak leg power which is a component of test batteries used to assess physical ability [21]. Both measurements are inexpensive, easy and reliable method of muscular strength assessment [16,22,23].

In recent studies, handgrip strength is reported to be differed significantly across ethnic groups, with lower handgrip strength associated with higher prevalence of type 2 diabetes mellitus [24,25]. This highlights the importance of ethnic-specific reference standards for screening and monitoring purposes. Normative data for handgrip strength and/or vertical jump have been developed for children in different countries [22,26-31]. Only one recent publication from China mainland reported the reference data of the muscular strength [32]. However, the association between muscular strength and the Anthropometric measurements was note addressed in this report. Among the published reports, few explored this association [22,26,33]. Furthermore, muscular strength is correlated with BMI and, particularly, muscle mass [34]. However, this could simply reflect the gender difference because of the effect of sex steroid hormones [35,36]. In fact, scientific evidence suggests that Asians have different associations between weight status, body composition and health risks than do European populations. For example, in some Asian populations a specific BMI reflects a higher percentage of body fat than in white or European populations [37]. The association of muscular strength, weight status, and body composition in Hong Kong Chinese children and adolescents is not known. In this study, we aimed to examine the associations of handgrip strength and vertical jump with gender, anthropometric variables and body composition. We also establish normal reference values for handgrip strength and vertical jump for Hong Kong Chinese children.

Materials & Methods

Design

This cross-sectional study measured grip strength in a cohort of healthy children and adolescents. The data were used to generate normative values for handgrip strength and vertical jump.

Subjects

This was a part of a territory-wide cohort study on 24-h ambulatory blood pressure of Chinese children and adolescents conducted in 2011 to 2012 [37]. A two-stage cluster sampling method was used. Data from the Education Bureau, the government of the Hong Kong Special Administrative Region, were used to compile a sampling frame of all schools in Hong Kong. In the first stage, one primary school and one secondary school were randomly selected from each of the 18 Districts in Hong Kong. In the second stage, students were selected randomly by computer generated numbers and were invited to join the study. Details were mentioned in our previous publication [37]. An information sheet explaining the purpose and procedure of the study was given to each child and his/her parents. All children completed a validated self-reported Pubertal Development Scale [38]. Informed assent was obtained from the children and consent from their parents before the measurements. This study was approved by the Joint Chinese University of Hong Kong and New Territories East Cluster Clinical Research Ethics Committee. (CRE-2009.540)

Procedures

Anthropometric Measurements

A team of three trained research staff visited each selected school on a pre-arranged date for data collection. Standing height without shoes was measured using a stadiometer (seca 217, UK) to the nearest 0.1 cm. Body weight and percentage body fat were measured with light clothing using foot-to-foot bio-electrical impedance by a validated electronic body composition analyzer (Model BF-522, Tanita, Japan) [39,40]. Children emptied their bladder before the measurement. They were asked to stand barefoot on the metal sole plates of the machine, and gender and height details were entered manually into the system. Body weight and percentage body fat, estimated using the standard built in prediction equations for children, were displayed on the machine and printed out. Body mass index was converted to z score using local normal reference [41]. Children were classified into underweight, normal weight, overweight or obese based on their body mass index (BMI) using the International Obesity Task Force cut-offs [42]. Percentage body fat was also converted to z score using local normal reference [40]. Children were categorized into high and low body fat groups using the 85th percentile of the local reference as the cutoff [40].

Handgrip Strength

Handgrip strength was done by an assessor with background of Sports Science and Physical Education. Each subject was given a brief demonstration and verbal instructions for the handgrip strength test using the Takei T.K.K.5001 GRIP-A handgrip dynamometer (Takei Scientific Instruments Co. Ltd, Tokyo, Japan). The dynamometer was adjusted according to the child’s hand size. The test was done in the standing position, with the wrist in the neutral position and the elbow extended. Subjects were given verbal encouragement to ‘squeeze as hard as possible’ and apply maximal effort for at least 2 seconds. Two trials were allowed in the dominant arm and the highest score recorded as peak grip strength (kg) [43]. Limb dominance was determined by asking the children whether they are left-handed or right-handed.

Vertical Jump

Vertical jump skill was assessed by means of the process-oriented method proposed in the Western Australian Teachers Resources [Department of Education Western Australia (EDWA), 2013] done by two trained assessors. A demonstration of how to jump was provided to each subject and he/she was allowed to practice the jump until meeting the jump criteria, which usually takes two jumps. The jump was a countermovement jump with the use of arms. The jump began from a standing position, keeping the feet flat on the ground, with the preferred shoulder adjacent to a wall. Standing reach height was obtained by asking the subject to reach up with his/her hand as high as possible to touch the wall. After that, the child bent knees to about a 90 degree angle while moving their arms back in a winged position; then thrusted forward and upward and touched the wall at the highest point of the jump. The results of the jump was measured and recorded on a centimeter scale (cm).Vertical jump score was calculated as the difference in distance between the standing reach height and the jumping height. Two jumps using the correct technique were allowed for each subject and the best score was retained for analysis [30].

Statistical Analysis

Statistical analyses were performed using PASW Statistics 21.0 (IBM SPSS Inc., New York, USA). Percentile curves were constructed using LMS method [44]. The LMS method estimates the measurement centiles in terms of three age-sex-specific cubic spline curves: the L curve (Box-Cox power to transform the data that follow a Normal distribution), M curve (median) and S curve (coefficient of variation). In brief, if Y(t) denotes an independent positive data (e.g. handgrip) at age t, the distribution of Y(t) can be summarized by a normally distributed SD score (Z) as follows:

Once the L(t), M(t), and S(t) have been estimated for each parameter at age t, the 100α th centile at t age could be derived from

C100α(t) = M(t) [1 + L(t)S(t)Zα]1/L(t)

where Zα is the α centile of the Normal distribution (for example for the 95th centile, α = 0.95 and Zα = 1.65). The LMS program (version 12.43, Institute of Child Health, London, UK) was employed to fit the data.

The Q-Q test was used to assess the normality of the anthropometric, handgrip and vertical jump variables (p > 0.05). Estimated marginal means for handgrip strength and vertical jump were generated and age and gender interactions were determined using two-way analysis of covariance (ANCOVA) with mass and stature as covariates. General linear model was used to evaluate the effects of age, sex, pubertal stage, body size, body fat and the possible 2-way interactions on handgrip strength and vertical jump. Significance level was set at p <0.05.

Sample Size Calculation

Assuming both handgrip strength and vertical jump are normally distributed among each age and gender, sample size was calculated in terms of the standard deviation of the 100th centile (SDc100) and the age- and gender-specific SD described by Healy [45] as:

where k is the appropriate value from the standard normal distribution. For 97th centiles, k = 1.88.

To find out the age and gender-specific means and SDs for sample size calculation, pilot data were collected from 200 healthy children aged 8-17 years. The required sample sizes for each gender and age group to obtain an extreme centile, i.e. the 97th centile, with an error of 4% were listed in supplementary table. The estimated total number of subjects required for handgrip strength and vertical jump are 944 and 794, respectively (S1 Table).

S1 Table:  Handgrip strength and vertical jump data collected from 200 healthy children aged between 8-17 years.

Results

Subject Characteristics

A total of 1175 subjects aged 8-17 years from 32 schools (14 primary and 18 secondary schools) participated in the study. Twenty-one students were excluded due to incomplete data. The remaining 1154 subjects (49.3%, 569 boys) were included in the final analysis. Sex- and age-specific characteristics are shown in (Table 1). No subjects had any previous history of metabolic disease, and no participants were taking any type of medication. The mean ± SD age for boys and girls were 12.6y ± 2.7 (range: 8.2–17.9y) and 12.7y ± 2.8 (range: 8.1–17.9y) respectively.

According to the BMI cutoffs from the International Obesity Task Force (IOTF) [42], 13.9% (160/1154), 65.4% (755/1154), 15.1% (174/1154) and 5.6% (65/1154) of subjects were classified as underweight, normal weight, overweight and obese, respectively. The prevalence rate of overweight or obesity (20.7%) in our cohort of children was similar to that (20.4%) obtained from the previous Hong Kong Student Health Service Survey in 2008/2009 [3]. A total of 235 (20.4%) subjects were classified as having high percentage body fat, of whom 184 were overweight/obese and 51 were normal weight by IOTF definitions.

Table 1: Subject characteristics of 1154 children by age and sex.

Figure 1: Smoothed centiles curves of handgrip strength for Hong Kong Chinese Children aged 8 to 17 years.

Figure 2: Error bar charts of handgrip strength by age and sex *indicates significant sex difference, p <0.05.

Figure 3: Error bar charts of handgrip strength by pubertal stage and sex *indicates significant sex difference, p <0.05.

Handgrip Strength

The smoothed age-specific centile curves for boys and girls are shown in (Figure 1). General linear model revealed that handgrip strength was positively associated with age (F=1763, p <0.001), male sex (F=96.8, p <0.001) and the age*sex interaction (F=159, p <0.001). The age- and sex-specific error bar chart demonstrated that the sex difference was significant for subjects aged 13 years or older. (Figure 2) The pubertal stage*sex interaction was also significant (F=22.5, p <0.001). Significant sex differences were observed in subjects of pubertal stage III or later. (Figure 3)

BMI z score was positively associated with handgrip strength (F=12.9, p <0.001). The interaction between BMI z score and body fat z score was also significant (F=12.9, p <0.001). Further analysis revealed that among overweight/obese children, those with high body fat had significantly lower handgrip strength than those with low body fat [estimated marginal mean (SE): 18.0kg (0.5) c.f. 20.3kg (1.0), p = 0.039].

A full model including age, sex, BMI z score, body fat z score and age*sex interaction explained 67.8% of the variance of handgrip strength. The model demonstrated that handgrip strength was positively associated with age, male sex and BMI z score, but was negatively associated with body fat z score. (Table 2) The BMI z score*body fat z score interaction became insignificant (p = 0.83) in the fully adjusted model.

Figure 4: Smoothed centiles curves of vertical jump for Hong Kong Chinese Children aged 8 to 17 years.

Figure 5: Error bar charts of vertical jump by age and sex *indicates significant sex difference, p <0.05.

Figure 6: Error bar charts of vertical jump by pubertal stage and sex *indicates significant sex difference, p <0.05.

Table 2: Significant correlates of handgrip strength and vertical jump

Vertical Jump

The smoothed age-specific centile curves for boys and girls are shown in (Figure 4). General linear model revealed that vertical jump was positively associated with age (F=800, p <0.001), male sex (F=116, p <0.001) and the age*sex interaction (F=229, p <0.001). The age- and sex-specific error bar chart demonstrated that the sex difference was significant for subjects aged 12 years or older. (Figure 5) The pubertal stage*sex interaction was also significant (F=36.0, p <0.001). Significant sex differences were observed in subjects of pubertal stage II or later. (Figure 6) Vertical jump was positively associated with BMI z score (F=9.5, p = 0.002) but negatively associated with body fat z score (F=16.7, p <0.001). The interaction between BMI z score and body fat z score was not significant (F=2.1, p = 0.15).

A full model that included the same list of factors as those correlated with handgrip strength, i.e. age, sex, BMI z score, body fat z score and age*sex interaction, explained 60.1% of the variance of vertical jump. (Table 2) The model demonstrated that vertical jump was positively associated with age, male sex and BMI z score, but was negatively associated with body fat z score. (Table 2)

Discussion

We established age and gender specific normative values of handgrip strength and vertical jump in Hong Kong Chinese children. Although another report has provided normative data previously [32], the subgroups according to age and gender only mean and standard deviation were shown in most studies [46]. Handgrip strength and vertical jump increase with age in both genders, with boys stronger than girls particularly after the age of 12 years.

Similar to previous investigations, maximal handgrip strength was measured in ACFIES [43], EUROFIT [47] and CHMS [48], while the maximal jump height was reported in a sample of English school children [30]. Our results are close to the Britain children in both handgrip strength [43] and vertical jump [30]. As expected, our result was very different from those of CHMS, performed in Canadian children with handgrip strength between 24 and 89 kg in boys and between 21 and 56 kg in girls aged 8–19 years old [48]. Our finding indicates the importance of having a reference value for different populations.

In regard of the gender difference, body composition is largely due to the action of sex steroid hormones [35], probably leading to a difference in muscular strength. Nevertheless in boys, growth hormone and testosterone have more effects on muscular strength than in girls [49]. In our study, age, gender, BMI, and body fat were important predictors of handgrip strength and vertical jump, which were in line with previous findings from other countries [22,26-31]. There were only a few reports on the associations between handgrip strength and weight status [22,26]. Our finding was similar to these studies [22,26] that handgrip strength increased with weight status, as reflected by BMI. Importantly, our further analysis showed that overweight and obese children with high body fat had significantly lower handgrip strength compared to their overweight and obese peers with low body fat. Our study also found that vertical jump was positively associated with BMI but negatively associated with body fat. Children who were heavier, or being classified into overweight and obese categories, may have increased or no increased lean muscle mass in addition to fat [50], that the increased lean muscle mass may contributes to the better performance of handgrip strength and vertical jump.

BMI, as a measure of weight adjusted for height, correlates with body fat and with cardiovascular risk factors in children and adolescents, and a high value also predicts future adiposity, morbidity and death [51], Although BMI is the most widely used surrogate measure for screening for obesity, it cannot distinguish between fat mass and lean muscle mass. Thus, individuals with increased muscle mass may have increased BMI and although classifying as overweight their body fat level may still within normal range and they have low risk for cardiovascular risk factors. In our sample, about 20% of the children we tested fell into this category. It highlights the importance that when classifying children’s weight status by BMI cutoffs, additional information on children’s body composition such as percentage body fat, or fat-free mass should also be considered.

This study has some limitations. Our findings should be interpreted with caution as it is a cross-sectional study, it cannot demonstrate cause-and-effect. A longitudinal study is required to assess the longer-term health outcomes which may be associated with handgrip strength and vertical jump. Second, we utilized bioelectrical impedance as a measure of percentage of body fat and this technique is not without its limitations in children. Poor validity and measurement error have been reported [52], although, previous work in the same population has shown it is an adequate surrogate for percentage of body fat when compared to dual x-ray absorptiometry [53].

Advantages of this study include – huge sample size and pretty representative of the territory. It is noteworthy considering handgrip strength and vertical jump as a physical fitness test battery for the schoolchildren because it is more likely to be implemented in normal physical education settings.

Conclusion

The reported data enables health professionals to identify children and adolescents with poor strength according to age, gender and body composition, and to evaluate the effects of therapeutic interventions. Reference values for handgrip strength and vertical jump are provided for Hong Kong Chinese children and adolescents aged 8 to 17 years.

Acknowledgments

We would like to express our gratuities to Mr. Tsang Fan Pong for his help on data collection. We thank the school principals, teachers, parents and students for their support and help for this study. The project is supported by the Health and Health Service Research Fund (they now renamed Health and Medical Research Fund since December 2011) [Ref no: 08090141], Food and Health Bureau, Hong Kong SAR Government, Peoples’ Republic of China.

Authors’ Contributions

CCWY led the study conception and designed the study, participated in the coordination and execution of the study, and drafting, writing, and revising of the manuscript; HKS participated in coordination and execution of the study and drafting, and revising of the manuscript; CTA contributed to the acquisition of data analysis and interpretation of data; AMM, AML and RYTS participated in conceptualizing and designing the study, and revising of the manuscript. All authors have read and approved the final version of the manuscript, and agree with the order of presentation of the authors.

More information regarding this Article visit: OAJBGSR

https://biogenericpublishers.com/pdf/JBGSR.MS.ID.00166.pdf

https://biogenericpublishers.com/jbgsr-ms-id-00166-text/

For more open access journals click on https://biogenericpublishers.com/