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Android vs gynoid body fat distribution influence on fitness goals

Android vs gynoid body fat distribution influence on fitness goals

Vody, we showed that the Andrroid of aerobic exercise to WL results in greater reductions in 2-h insulin than WL alone [ 12 Weight management for emotional eaters. Bone, pp. Android vs gynoid body fat distribution influence on fitness goals IA, Dick TJ, Diwtribution JA, Hoogbruin A, Mackey DC, Singer J, Lear SA: The association between cardiorespiratory fitness and abdominal adiposity in postmenopausal, physically inactive South Asian women. This can be found under your skin, between the organs, and all throughout the body. The models included group, time, and group × time interaction set as fixed variables. Read on to know how you can help fix the beauty industry and create positive experience.

Android vs gynoid body fat distribution influence on fitness goals -

Several parameters can be used to compare these types of obesity that find a way to present themselves in adult males and females.

Table of Contents. Obesity in the male android type presents itself dominantly around the visceral and upper and middle back or the thoracic regions of the body. The fat is deposited around the central trunk region mid-section and stomach and can also include the chest and arms.

Android obesity, since it sees fat in the chest and arm region of the body, can also be linked to insulin resistance. This could mean that the body may not be able to transport and use the extra sugar and glucose molecules present for energy.

Since the glucose is not used, it floats in the blood leaving the body susceptible to diabetes. Android type of fat is also commonly associated with other medical conditions like heart diseases, hormonal imbalances, sleep apnea, etc. A strong reason for the association of different medical conditions with this type of fat is the high correlation of android fat with a high amount of visceral fat.

The more visceral fat, the higher the release of proteins and certain hormones that trigger inflammation in the body. This inflammation can damage arteries and can also invade our organs and affect the vital processes that they carry out each minute.

Gynoid obesity, on the other hand, is more commonly found in females. It can be characterized as a higher amount of fat accumulation around the hips, breasts, and thighs.

A person who is obese gynoid type has a pear-shaped body. It has different causes and health consequences as opposed to the android type. Females are more susceptible to developing this type of obesity due to the natural gynoid fat that exists in their bodies which aims to provide nourishment to the offspring.

Gynoid fat can also be termed reproductive fat. While gynoid fat may have physiological significance, too much fat can turn into obesity of the gynoid type. One can also find this type of obesity in males, however, it is very rare.

Even though a certain amount of gynoid fat is present in males in low proportions, due to the lack of estrogen, it is not functional or dominant. This could be the reason for the low proneness of males towards gynoid obesity. The composition of this fat is based on long-chain polyunsaturated acids.

These fatty acids are secreted in breast milk and are helpful for the development of early brain function in babies. Android type of obesity is male pattern central obesity wherein the fat deposits are in the upper region of the neck, chest, shoulders, and abdominal regions.

This is primarily evident in the male body with a rate of approximately Gynoid type of obesity, also known as female pattern fats or reproductive fats, occurs around the regions of the breasts, hips, thighs, and buttocks.

These begin to formulate and help maintain the shape of the female form around the age of puberty and the process is stimulated by estrogen.

Android fats are caused due to genetic factors. Gynoid fats are present and are functional due to estrogen. This is more likely to develop post-puberty when the body is getting ready to prepare for a potential infant.

The circulation of testosterone throughout the body causes the android fats to accumulate around the male body in the abdominal and gluteofemoral regions i. Perform each exercise for 30 seconds, with a second rest in between to remain in the aerobic-training zone.

Repeat the cycle two to four times to keep the heart rate up and calories burning. Rest one to two minutes in between each cycle. Using a treadmill or short hill, do to second intervals RPE of on a scale of 10 five to 10 times. Walk for 60 to 90 seconds in between each interval.

If you do two sets of five sprints, rest five to 10 minutes between sets by doing active recovery walking, or light jogging. Jacque Crockford, DHSc, is an ACE Certified Personal Trainer and Senior Product Manager at ACE. She has been a personal trainer and performance coach for 20 years. Jacque grew up in the fitness industry, participating in YMCA sports and teaching gymnastics and swimming from a young age.

Sign up to receive relevant, science-based health and fitness information and other resources. Get answers to all your questions! Things like: How long is the program? Program Design. Body Type Workouts: How to Train Clients With an Android Body Type.

by Jacqueline Crockford, DHSc on June 05, Filter By Category. View All Categories. View All Lauren Shroyer Jason R. Karp, Ph. To calculate Matsuda index, insulinogenic index and the disposition index, 30 min values for glucose and insulin were estimated using the 20 min and 40 min values.

Analyses were completed in Stata version Stata Statistical Software: Release The data reported in this manuscript were collected as part of a larger study. Several the outcomes have been published previously Valsdottir et al. Some of the results that were presented in the earlier paper are provided to some degree in the present manuscript to assist with interpretation of the results.

For data that have previously been reported the information is stated below tables. A study flow chart of enrollment and participant flow, as recommended by the Consolidated Standards of Reporting Trials CONSORT has been published elsewhere Valsdottir et al.

Screening took place from October to January , while the intervention was conducted from January 27 to 7 April In total, 60 women were eligible for participation; however, three women withdrew during the 3-week run-in with baseline measurements.

One participant did not adhere to the NORM diet protocol; one withdrew due to a work situation and two gave no reason for withdrawal.

Baseline characteristics for participants in each of the intervention groups are shown in Table 1. Detailed data for weight loss have previously been reported Valsdottir et al. Briefly, the intervention resulted in similar weight losses in all groups, with no differences between groups.

Within-group comparison showed that all four groups achieved a weight loss in response to the energy deficit during the intervention.

The weight loss was as follows: NORM 5. The weight loss was 6. FIGURE 2. Weight loss during the intervention, measured every 2 weeks. Data are presented as mean ± standard deviation SD. NORM, Normal diet; LCHF, Low-carbohydrate high-fat diet; NORM-EX, Normal diet combined with exercise; LCHF-EX, Low-carbohydrate high-fat diet combined with exercise.

Cardiorespiratory fitness results have previously been reported Valsdottir et al. This data is included only to facilitate the interpretation of current results. Between-group differences in cardiorespiratory fitness were observed comparing NORM and NORM-EX group Table 2.

The difference was a result of an increase in the NORM-EX group, combined with a decrease in the NORM group.

Within-group comparison showed a robust increase in the exercise groups in response to the intervention. TABLE 2. Ancillary analysis: Cardiorespiratory fitness at baseline and after the week intervention.

Between-group comparison showed no difference in AUC glucose in response to the week intervention Figure 3A. Between-group comparison showed no difference in AUC insulin in response to the week intervention Figure 3B. FIGURE 3. Primary outcome glucose tolerance measured as Area Under Curve AUC A glucose, and B insulin, during a min oral glucose tolerance test OGTT prior to the intervention pre and after post the week intervention.

Between-group comparison showed no difference in fasting glucose after the week intervention Table 3. The other groups did not show any significant response to the intervention Table 3.

TABLE 3. Primary outcome: Fasting values for glucose and insulin, and markers of insulin resistance at baseline and after the week intervention. Between-group comparison showed no difference in HOMA-IR after the week intervention Table 3. No significant changes were observed within the other intervention groups Table 3.

Between-group comparison showed no difference in Matsuda ISI after the week intervention Table 3 ; Figures 4A, B. FIGURE 4. Time course prior to pre and after post the week intervention for glucose A and insulin B during a minute oral glucose tolerance test OGTT.

Between-group comparison showed no differences in neither insulinogenic nor disposition indicis after the intervention Table 3.

Between-group comparison showed a significantly lower mass of android fat in the LCHF group, when compared with the NORM group after the week intervention Table 4.

TABLE 4. Secondary outcomes: Android fat, gynoid fat, and lean body mass at baseline and after the week intervention. Between-group comparison showed no difference in gynoid fat mass after the week intervention Table 4.

Within-group comparison showed that all groups achieved a reduction in gynoid fat mass in response to the intervention Table 4. No unintended or serious effects were reported. Well-known minor and non-serious side effects of the LCHF diet were reported during the first 2 weeks.

The main finding in our study was that weight loss achieved with combined LCHF diet and exercise, caused no superior improvement in glucose tolerance after a week intervention. Indeed, the intervention resulted in no differences in glucose tolerance when comparing the intervention groups.

The results indicate that improvements in glucose tolerance, measured as AUC, are not attributable to either specific diet or exercise. Rather, the improvements seem to be a combined effect of exercise and diet resulting in weight loss.

Our results are in line with previous studies, showing no improvements in AUC glucose when comparing a calorie restricted diet and a calorie restricted diet plus exercise Schenk et al.

Prior to the study, we speculated an additive effect of weight loss, exercise and LCHF diet on glucose tolerance. This hypothesis was based on previous findings that separately showed positive effect on glucose tolerance by exercise Jenkins and Hagberg, ; Bird and Hawley, ; Malin et al.

Therefore, we anticipated significant improvements in the exercise groups compared to diet-only groups, with superior effects on glucose tolerance in LCHF-EX. However, our study did not reveal differences among the groups, presumably as a result of smaller improvements in AUC glucose than hypothesized.

Within-group comparisons showed improved AUC glucose in both exercise groups, in addition to the NORM group. Results from the present study show that the three groups with a significant reduction in AUC glucose had post levels close to baseline levels in females with normal weight.

The positive effect of exercise on glucose tolerance is short lived and transient and must be maintained with repeated bouts of exercise, with no longer than 48—72 h between sessions The present results indicate that improvements in glucose tolerance are relatively long-lived and detectable after 36 h post exercise in this population.

Nevertheless, the effects of exercise were possibly starting to fade in the exercise groups. This indicates that a bout of exercise must be repeated regularly to maintain improvement in glucose tolerance, and possibly achieve chronic improvement.

It is noteworthy that the NORM group exhibited AUC values within the normal range after the intervention Valsdottir et al.

The lack of improvement in glucose tolerance in the LCHF group, contrary to improvements in the NORM group, can be explained by decreases in rates of carbohydrate oxidation due to adaptation to the LCHF diet. This is supported by Burke et al. Notably, Kirk et al. The robust improvement observed in LCHF-EX may relate to the positive effect of exercise on glucose uptake in skeletal muscle Rose and Richter, , as the comparable LCHF did not show any improvement in glucose tolerance.

The reduction in AUC in LCHF-EX was expected in response to the exercise, and in accordance with previous observations in overweight males Jelstad et al.

The results from that project formed the basis for the sample-size calculations in this study. However, improvements in glucose tolerance may be gender-specific, as Metcalfe et al.

The various results in AUC glucose after lifestyle interventions can be related to several factors, including initial body weight, total weight loss, gender, age, exercise intensity and timing of glucose tolerance testing after the last bout of exercise.

AUC insulin showed a similar pattern to AUC glucose in this study, with no differences among the groups. However, a robust within-group reduction was observed in both exercise groups, with no improvement in the diet-only groups. As exercise stimulates non-insulin-dependent glucose uptake Kjobsted et al.

Considering the lack of difference between-group s, we cannot conclude that inclusion of exercise in weight-loss programs will improve AUC insulin in this population.

Previous studies with regular exercise for participants with overweight and obesity have shown improvements in AUC insulin Jelstad et al. However, the positive effect of exercise on glucose disposal is essential, as the reduction of pancreatic secretion of insulin may be an important factor in preventing T2DM later on in life.

High production of insulin over time has been linked to reduced function of ß-cells and pancreatic failure Abdul-Ghani and DeFronzo, This week intervention provided divergent results in terms of fasting glucose among the intervention groups, although no between-group differences were observed.

Improvements in fasting glucose have been seen in response to both a bout of exercise and prolonged exercise program, with and without weight loss Keshel and Coker, Nevertheless, our study showed no effect of exercise on fasting glucose, as no difference was seen between the LCHF and LCHF-EX nor NORM and NORM-EX groups.

Improved fasting glucose is one of the most noticeable responses to weight reduction Clamp et al. In weight-loss studies of subjects with prediabetes, low-carbohydrate diets have been superior to low-fat diets in lowering fasting glucose Kirkpatrick et al.

However, after this period the differences faded, allegedly a consequence of the gradual increase in carbohydrate intake in most LCHF diets, after the induction ketosis phase Atkins, ; van Wyk et al.

Others have shown an additive effect of diet and exercise for reducing fasting glucose Weiss et al. However, this was not the case in our study, despite our participants staying well below g of carbohydrates throughout the intervention.

Several factor can explain lack of differences between groups, such as normoglycemic participants at baseline Serra et al. These amounts are equal to, and above the limits for LCHF diets and may possibly change the positive effects previously seen on fasting glucose during LCHF diets.

Regardless of the absence of between-group differences, we observed within-group improvements in fasting glucose in the LCHF-EX group. Others have shown that both LCHF diets and exercise had positive effects and reduced fasting glucose Kirkpatrick et al.

While LCHF-EX was the only group to achieve improvements in the current study, it must be emphasized that this group also showed the highest level of fasting glucose prior to the intervention and reached baseline levels comparable the other groups, after the intervention.

On the contrary, Shai et al. The denominator for large improvements in fasting glucose seems to be high glucose at baseline, giving room for more pronounced reduction in response to an intervention and possibly explaining the lack of improvement in the LCHF diet group versus the comparable exercise group LCHF-EX , without between-group differences.

Our protocol included testing towards the lower end for positive effect of exercise, and it is therefore plausible that the only group that achieved positive effect was the one with the most unfavorable baseline levels.

All groups were within the normal reference range prior to the intervention, and improvements in normal values are not decisive for primary T2DM prevention. The intervention did not result in differences between groups, and no improvements were seen within groups.

This is in line with Gilbertson et al. However, Weiss et al. Fasting insulin levels however, are associated with large individual variations without individuals being insulin resistant or having reduced glucose tolerance Festa et al. LCHF-EX was the only group to attain a significant improvement in HOMA-IR despite equal weight loss in all groups.

Nevertheless, LCHF-EX was the only group to exhibit HOMA-IR above cut-off values of 2. The low and non-significant improvements in glucose and insulin in the other groups are reflected in the HOMA-IR, and similar lack of improvement has previously been observed by Gilbertson et al. Despite the lack of significant improvements within NORM, LCHF and NORM-EX, these groups achieved a reduction in HOMA-IR, with post values below the cut-off point for hepatic insulin resistance Radikova et al.

This demonstrates a beneficial impact on insulin sensitivity and cardiometabolic health Hallberg et al. Figure 4 shows a glucose and b insulin time course for all groups, pre and post intervention. The Matsuda ISI is used to estimate peripheral skeletal muscle insulin sensitivity Matsuda and DeFronzo, The intervention did not result in between-group differences in the Matsuda ISI.

However, w ithin-group improvement was observed in the exercise groups, in addition to the NORM group. In addition, all groups to reached values higher than the cut-off level of 5, which is regarded as appropriate to maintain a healthy insulin sensitivity.

Our results show that weight-loss with or without exercise increases peripheral insulin sensitivity. Yet, due to the lack of between-group differences we cannot state that exercise has superior effect than diet only. Noteworthy, our study was powered for AUC glucose as primary outcome so considering the larger increase in Matsuda ISI the exercise groups, it is plausible that the inclusion of exercise in lifestyle interventions should be preferred to achieve weight loss and improve insulin sensitivity.

The insulinogenic index is used as an index for early phase insulin secretion and is a reasonable surrogate for acute insulin response AIR Aono et al.

However, improvements above the normal baseline levels can be difficult to reach. The disposition index can be used to assess β-cell function during an OGTT and identifies β-cells deficiency and the inability to compensate for insulin resistance.

A low disposition index is an early marker of faulty β-cells and predicts a development to T2DM, beyond fasting glucose levels Abdul-Ghani et al. Previous studies have shown that the disposition index and first-phase insulin are not affected when adjusted for visceral adiposity and BMI Burns et al.

After the intervention, between-group comparisons showed larger reductions in android fat mass in LCHF compared to NORM, indicating a positive effect of the LCHF diet.

However, this did not affect the glucose tolerance positively. Differences in android fat mass were observed between NORM and LCHF, but not between NORM-EX and LCHF-EX.

Hence, we cannot attribute any positive effects of the LCHF diet on android fat, or on the primary outcome glucose tolerance.

This is supported by previous research where high-carbohydrate and high-fat diets did not differentially influence android visceral fat area Veum et al.

Android obesity in females has been related to reduced insulin sensitivity Wiklund et al. Nevertheless, even with substantial improvement in android fat in LCHF, no improvement was observed in glucose tolerance in this group.

Previous research has shown that android and gynoid fat have opposite associations with CVD and other metabolic risk factors Lumish et al. It should be noted that gynoid fat as compartment often reflects a linear relationship with total fatness and increased CVD risk Fox et al.

Indeed, studies of females with normal weight have shown that joint occurrence of elevated android and gynoid fat percentage is associated with higher odds for elevated glucose than high android fat alone Okosun et al.

The present intervention resulted in a substantial reduction in both android and gynoid fat in all groups.

However, the persisting high percentage of body fat, likely prevented a significant improvement in glucose tolerance, as gradients of adiposity have been shown to increase the numbers of CVD risk factors Okosun et al. Data for weight have been published elsewhere Valsdottir et al.

This can be explained by several factors, such as overestimating PAL and calorie requirement at baseline and a greater energy intake than assessed by diet records. Previous studies have observed some underreporting, with a greater bias in females and individual who are obese and weight-conscious Schoeller, ; Millen et al.

Recent studies have unveiled a possible link between the gut microbiome and weight gain Aoun et al. Others have suggested that energy deficit results in adaptive reduction in thermogenesis and resistance to losing weight Muller et al.

Although the main factor conceded during weight-loss, is adherence to the prescribed energy deficit, the genetic component will influence the ability to respond. The development of overweight and obesity has a strong genetic component which also can cause resistance to lose weight Lamiquiz-Moneo et al.

Further on, Bouchard et al. All aforementioned factors are plausible, but outside the scope of this manuscript. A reduction in cardiorespiratory fitness after weight-loss without exercise has been observed by others Goran et al. The reduction appears to develop due to reduced body mass that results in lesser cardiorespiratory demand during daily activities.

A similar pattern is evident in women, although not detectable in conservative models. Despite weaker association in women, the potential modifying role of cardiorespiratory fitness on obesity mortality supports the inclusion of sufficient physical activity in lifestyle interventions.

The strengths of this study are the inclusion of females only, and the high compliance with the exercise program. Another strength is the tight supervision of both diet and exercise. Some limitations must also be acknowledged. In our power calculation we anticipated an improvement in AUC of ± mean ± SD.

However, the greatest improvement in AUC was U in LCHF-EX. Due to this modest improvement, no between-group differences were detected.

Hence, it can be argued that this study was underpowered to detect such modest improvements, potentially resulting in type II error. Weiss et al. Unfortunately, this was not possible with the present design, as increased exercise sessions in the exercise groups would induce larger effects on parameters linked to weight-loss and cardiorespiratory fitness.

Another study limitation is that the exercise groups got additional interactions compared to the diet-only groups, as these participants both mingled and met with the staff and researchers three times weekly during exercise sessions. This study did not control for the greater amount of personal contact time received by the exercise groups relative to the diet-only groups.

Moreover, we did not control the timing of testing relative to menstrual phase, which may increase variability in glucose tolerance MacGregor et al. In view of the positive effect of increased physical activity during the intervention, the lack of monitoring daily physical activity of participants must be considered as a limitation in this study.

Matched weight loss during a week program with diet only, or with a combination of exercise and diet, resulted in improvements exclusively in the exercise groups, in terms of cardiorespiratory fitness and AUC insulin.

Collectively, these results emphasize the positive effects and importance of exercise during a weight-loss program. As the current study was designed to compare the effectiveness of the intervention groups, the main conclusion for between-group comparisons showed no superior effect for any of the intervention groups with regard to the primary outcome glucose tolerance AUC glucose.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. The project was funded by Atlantis Medical University College and Norwegian School of Sports Sciences as a part of a PhD education.

The authors thank Marius Dahl and Øyvind Skattebo for their assistance during exercise sessions and Kathrine Aas Krog and Ellen Rael for their assistance in the laboratory.

The authors also thank Linda Knutson, Sigrid Heldal, Ida Lobben Stie, Camilla Steinhovden, and Anniken Hjelbakk Hole for their help with nutritional guidance. In addition, the authors thank Marianne Holst for her help with graphics, Flemming Solberg for guidance in mathematical presentation and Asgeir Mamen for great discussions and advices.

Thomas Haugen gets a special thanks for comments that greatly improved the manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abdul-Ghani M. Pathophysiology of prediabetes.

Disfribution study was boey to fah the effects of weight loss induced by a low-carbohydrate-high-fat diet Anxroid a normal diet, with and without Lentils for hormonal balance, Android vs gynoid body fat distribution influence on fitness goals glucose tolerance measured as area under the curve AUCand android A and gynoid G fat distribution. The study was registered at clinicaltrials. gov ; NCT In total, 57 women classified as overweight or obese age 40 ± 3. There were thus four groups: normal diet NORM ; low-carbohydrate-high-fat diet LCHF ; normal diet with exercise NORM-EX ; and low-carbohydrate-high-fat diet with exercise LCHF-EX. Android vs gynoid body fat distribution influence on fitness goals

Author: Kagacage

3 thoughts on “Android vs gynoid body fat distribution influence on fitness goals

  1. Ich bin endlich, ich tue Abbitte, aber diese Antwort kommt mir nicht heran. Wer noch, was vorsagen kann?

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