Since alcohol contains calories, it can contribute to excess calorie intake and fat gain Some research has also shown that individuals who consume a lot of alcohol are more likely to be obese Additionally, some factors that affect body composition cannot be changed.

For example, both age and genetics impact body composition. However, since you cannot control these factors, it is probably best to focus on what you can control, like nutrition, exercise and sleep. You can get a more accurate picture by taking into account your body composition, or your fat mass and muscle mass.

Two simple ways to track your body composition over time include measuring the circumference of different body parts and taking progress pictures at regular intervals.

Your body composition is affected by your nutritional habits, exercise, sleep and other factors. For this reason, improving it can sometimes feel complicated. However, focusing on some of the basic concepts covered in this article can get you started in the right direction. Does muscle really weigh more than fat?

We also explain how to balance diet and lifestyle for…. Targeting heart rate zones as you exercise is one way to maximize the benefits you get from your workouts. Learn about your different heart rate zones…. There are several causes of numbness in your toes and feet when you run, ranging from poor-fitting shoes to health conditions like diabetes.

For people who run or do other aerobic exercises on a regular basis, starting up a low heart rate training program may be frustrating at first. The average 5K time depends on a few factors, including age, sex, and fitness level.

But, you can expect to finish a 5K in roughly 30 to 40 minutes. Thinking about using an AI tool like ChatGPT to help you get in shape? Here are the pros and cons health experts say you should consider.

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Nutrition Evidence Based How to Improve Body Composition, Based on Science. By Grant Tinsley, Ph. Many people dread stepping onto the bathroom scale. This article will explain what your body composition is and how to improve it, based on science.

What Is Body Composition? Share on Pinterest. How Can You Assess It? The most accurate methods are usually expensive and only used in research or medical centers. Tracking Body Circumference One technique is tracking the circumference of different body parts 2.

You can make these measurements using a cheap, flexible tape measure. Taking Progress Pictures Progress pictures are another popular way to get a big picture look at your body composition.

It is often difficult to notice changes in your body from one day to the next. Devices That Measure Body Composition In addition to these simple methods, there are devices you can buy that measure body composition.

National Institute of General Medical Sciences. What do fats do in the body? Centers for Disease Control and Prevention.

What causes type 2 diabetes? National Cancer Institute. Muscle types. American Cancer Society. Normal weight ranges: Body mass index BMI. Body mass index BMI. Health effects of overweight and obesity.

Holmes CJ, Racette SB. The utility of body composition assessment in nutrition and clinical practice: An overview of concurrent methodology.

American College of Sports Medicine. Kasper AM, Langan-Evans C, Hudson JF, et al. Come back skinfolds, all is forgiven: A narrative review of the efficacy of common body composition methods in applied sports practice.

Frija-Masson J, Mullaert J, Vidal-Petiot E, Pons-Kerjean N, Flamant M, d'Ortho MP. Accuracy of smart scales on weight and body composition: Observational study. JMIR Mhealth Uhealth. St-Onge MP, Gallagher D. Body composition changes with aging: The cause or the result of alterations in metabolic rate and macronutrient oxidation?

Schorr M, Dichtel LE, Gerweck AV, et al. Sex differences in body composition and association with cardiometabolic risk. Biol Sex Differ. Fenton A. Weight, shape, and body composition changes at menopause. J Midlife Health.

Brener A, Waksman Y, Rosenfeld T, et al. The heritability of body composition. BMC Pediatr. Amaro-Gahete FJ, De-la-O A, Jurado-Fasoli L, Ruiz JR, Castillo MJ, Gutiérrez Á. Effects of different exercise training programs on body composition: A randomized control trial. Scand J Med Sci Sports.

National Institute of Aging. How can strength training build healthier bodies as we age? Carbone JW, Pasiakos SM. Dietary protein and muscle mass: Translating science to application and health benefit. Ahmad S, Demler OV, Sun Q, et al.

Van Proeyen et al. Subjects performed a combination of moderately intense cycling and running exercise for 60 90 minutes, 4 days per week. After 6 weeks, the fed group significantly increased body mass by 1.

Follow-up work from the same lab employing the same basic training protocol but with subjects consuming an isocaloric diet based on 4-day dietary analysis showed no differences in body weight change between fasted versus fed conditions [ 8 ]. Recently, Gillen et al. Subjects were instructed to maintain their pre-intervention eating patterns throughout the study period.

At study s end, body mass remained unchanged from baseline but lower body fat was noted both in the abdominal and leg regions as well as the whole body level in both groups. No significant differences were found between conditions.

Our results are novel in that subjects consumed a supervised hypocaloric diet throughout the intervention period. Loss of body mass is predicated on shifting energy balance to favor expenditure over intake [ 3 ].

This is consistent with the First Law of Thermodynamics, which essentially states that energy is neither created nor destroyed, but rather changed from one form to another. Thus, our approach allowed for a controlled investigation of the effects of fasted exercise on body composition under conditions favorable for fat loss.

Moreover, to optimize the proposed benefits of training while fasted, exercise was performed at low-to-moderate intensities. This is consistent with acute research showing that lipolysis is blunted during performance of higher- [ 14 ],[ 26 ] but not lower-intensity exercise when carried out in the fed state [ 10 ],[ 11 ],[ 27 ].

Despite these accommodations, fasted exercise showed no beneficial effects compared to training post-prandially. The theoretical basis behind a fat-burning advantage to fasted exercise is predicated on increasing lipid oxidation during training bout.

However, this ignores the dynamic nature of the human body, which continually adjusts its use of substrate for fuel. There is evidence that a greater utilization of fat for fuel during a given time period is compensated by a greater carbohydrate utilization later in the day [ 28 ]. Hence, fat burning must be considered over the course of days not on an hour to hour basis to meaningfully assess its impact on body composition [ 29 ].

In support of this contention, Paoli et al. Food quantity and quality was identical between conditions over the ensuing hour recovery period. Consumption of breakfast for the fed condition resulted in a significant increase in respiratory exchange ratio RER compared to fasting 0.

However, at 12 hours post-exercise RER was significantly lower in the fed versus fasting condition and the difference remained significant after 24 hours. Any potential increases in fat oxidation from fasted exercise might be neutralized by an increase in the thermic effect of exercise from eating pre-exercise.

Lee et al. Employing a within-subject design, 10 male college students performed four experimental conditions in randomized order: low intensity, long duration exercise with GM; low intensity, long duration exercise without GM; high intensity, short duration exercise with GM, and; high intensity, short duration exercise without GM.

Results showed that consumption of the GM beverage increased excess post-exercise oxygen consumption to a significantly greater extent than exercise performed while fasted in both high and low intensity conditions.

Similar findings have been reported in other controlled trials [ 32 ],[ 33 ]. The study had several notable limitations that must be taken into account when attempting to draw evidence-based conclusions. First, the duration of the testing period was fairly short, lasting just four weeks.

While this period is certainly sufficient to attain significant fat loss, it remains possible that subtle changes between protocols would take more time to manifest. Given that mean weight loss across groups was somewhat less than anticipated, it seems reasonable to assume that subjects did in fact underreport the amount of calories consumed, which would explain the attenuated results.

Similarly, although subjects were instructed not to partake in any other structured exercise other than activities of daily living, there is no way to assure that they adhered to this request.

Third, the use of young women as participants raises the possibility of confounding by menstrual cycles. The fact that testing was carried out exactly one month apart provides some degree of confidence that this did not influence results. However, it is not uncommon for women to have irregular menses, which may have affected hydration status and thus altered body composition measures.

Fourth, the FASTED subjects consumed nutrients immediately following training; it is not clear what, if any, impact would be seen on results by delaying consumption for longer periods post-exercise. Finally, results are specific to young, non-obese women and cannot necessarily be generalized to other populations.

For example, employing fasted-state, low- to moderate-intensity aerobic exercise is a popular tactic in physique sports where pushing extremes of leanness is one of the primary aims of contest preparation [ 35 ].

The applicability of the present study s results to such endeavors remains open to question. In conclusion, our findings indicate that body composition changes associated with aerobic exercise in conjunction with a hypocaloric diet are similar regardless whether or not an individual is fasted prior to training.

Hence, those seeking to lose body fat conceivably can choose to train either before or after eating based on preference. It should be noted that given the small sample size and short study duration, we cannot rule out the possibility that either condition might confer a small benefit over the other with respect to fat loss.

Further study is warranted in a longer term trial with a greater number of participants. BJS devised the study design, carried out the data collection, participated in the interpretation of data, and drafted the manuscript; AAA developed and implemented the nutritional protocol, participated in the interpretation of data and assisted in the writing the manuscript; CDW devised the dietary analysis, participated in the in the interpretation of data and assisted in the writing of the manuscript; JWK performed all statistical analysis, participated in the interpretation of data and assisted in the writing of the manuscript.

All authors read and approved the final manuscript. Donnelly JE, Blair SN, Jakicic JM, Manore MM, Rankin JW, Smith BK: American college of sports medicine position stand. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adults.

Med Sci Sports Exerc. Article PubMed Google Scholar. Wu T, Gao X, Chen M, van Dam RM: Long-term effectiveness of diet-plus-exercise interventions vs. diet-only interventions for weight loss: a meta-analysis.

Obes Rev. Article CAS PubMed Google Scholar. Hall KD, Heymsfield SB, Kemnitz JW, Klein S, Schoeller DA, Speakman JR: Energy balance and its components: implications for body weight regulation. Am J Clin Nutr. Article PubMed Central PubMed Google Scholar. Laye MJ, Thyfault JP, Stump CS, Booth FW: Inactivity induces increases in abdominal fat.

J Appl Physiol. Hunter GR, Brock DW, Byrne NM, Chandler-Laney PC, Del Corral P, Gower BA: Exercise training prevents regain of visceral fat for 1 year following weight loss.

Obesity Silver Spring. Article Google Scholar. Calabro P, Yeh ET: Intra-abdominal adiposity, inflammation, and cardiovascular risk: new insight into global cardiometabolic risk.

Curr Hypertens Rep. Gillen JB, Percival ME, Ludzki A, Tarnopolsky MA, Gibala MJ: Interval training in the fed or fasted state improves body composition and muscle oxidative capacity in overweight women.

Article CAS Google Scholar. Van Proeyen K, Szlufcik K, Nielens H, Ramaekers M, Hespel P: Beneficial metabolic adaptations due to endurance exercise training in the fasted state.

Kang J, Raines E, Rosenberg J, Ratamess N, Naclerio F, Faigenbaum A: Metabolic responses during postprandial exercise. Res Sports Med. PubMed Google Scholar. Horowitz JF, Mora-Rodriguez R, Byerley LO, Coyle EF: Lipolytic suppression following carbohydrate ingestion limits fat oxidation during exercise.

Am J Physiol. CAS PubMed Google Scholar. Ahlborg G, Felig P: Influence of glucose ingestion on fuel-hormone response during prolonged exercise. Civitarese AE, Hesselink MK, Russell AP, Ravussin E, Schrauwen P: Glucose ingestion during exercise blunts exercise-induced gene expression of skeletal muscle fat oxidative genes.

Am J Physiol Endocrinol Metab. Coyle EF, Jeukendrup AE, Wagenmakers AJ, Saris WH: Fatty acid oxidation is directly regulated by carbohydrate metabolism during exercise. Horowitz JF, Mora-Rodriguez R, Byerley LO, Coyle EF: Substrate metabolism when subjects are fed carbohydrate during exercise.

De Bock K, Derave W, Eijnde BO, Hesselink MK, Koninckx E, Rose AJ, Schrauwen P, Bonen A, Richter EA, Hespel P: Effect of training in the fasted state on metabolic responses during exercise with carbohydrate intake.

Van Proeyen K, Szlufcik K, Nielens H, Pelgrim K, Deldicque L, Hesselink M, Van Veldhoven PP, Hespel P: Training in the fasted state improves glucose tolerance during fat-rich diet.

J Physiol. Article PubMed Central CAS PubMed Google Scholar. Arciero PJ, Ormsbee MJ, Gentile CL, Nindl BC, Brestoff JR, Ruby M: Increased protein intake and meal frequency reduces abdominal fat during energy balance and energy deficit.

ACSM s Guidelines for Exercise Testing and Prescription. Schoenfeld B: Does cardio after an overnight fast maximize fat loss?. Strength Cond J. Frankenfield D, Roth-Yousey L, Compher C: Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review.

J Am Diet Assoc. Larsen TM, Dalskov SM, van Baak M, Jebb SA, Papadaki A, Pfeiffer AF, Martinez JA, Handjieva-Darlenska T, Kunesova M, Pihlsgard M, Stender S, Holst C, Saris WH, Astrup A: Diets with high or low protein content and glycemic index for weight-loss maintenance. N Engl J Med. Pasiakos SM, Cao JJ, Margolis LM, Sauter ER, Whigham LD, McClung JP, Rood JC, Carbone JW, Combs GF, Young AJ: Effects of high-protein diets on fat-free mass and muscle protein synthesis following weight loss: a randomized controlled trial.

FASEB J. McCrory MA, Gomez TD, Bernauer EM, Mole PA: Evaluation of a new air displacement plethysmograph for measuring human body composition. Maddalozzo GF, Cardinal BJ, Snow CA: Concurrent validity of the BOD POD and dual energy x-ray absorptiometry techniques for assessing body composition in young women.

Ballard TP, Fafara L, Vukovich MD: Comparison of Bod Pod and DXA in female collegiate athletes.

The total loss of lean mass during the MT averages 0. In concert, in the average SWAN participant, the accelerated increase in fat mass and decrease in lean mass results in a 3.

Jointly examining the rates of change in fat and lean mass during premenopause and the MT sheds light on why there is no measurable change in body weight trajectory accompanying the MT. The rate of increase in the sum of fat mass and lean mass is 0.

This is not a discernable change in rate, especially if bone loss during the MT which is not incorporated in the estimation of lean mass used here further lowers the MT slope estimate.

Framed alternately, the difference in slopes between premenopause and the MT for the sum of fat mass and lean mass is only 80 grams per year, while the difference in the slope of fat mass between premenopause and the MT is grams per year and the corresponding difference for lean mass is — grams per year.

Thus, although there are MT-related effects on body composition, we observe no acceleration in weight gain at the time of the MT. However, close examination of existing evidence suggests that it is inadequate to either support or refute the hypothesis that the MT influences body composition or weight 13 — Most directly comparable to ours are studies that gauged the impact of the MT on body composition or weight by examining these characteristics in relation to FMP time 17 , 19 , Using bioelectrical impedance, Sowers and colleagues did not detect an effect of FMP time on either fat mass or lean mass in a sample of women at the Michigan SWAN site Rather, they reported a linear increase in fat mass and a small, linear decrease in lean mass over time.

To investigate the relation between FMP time and weight, Davies et al. No effect of FMP time on weight was apparent; instead, the authors described a linear increase in weight with time.

Finally, in an analysis of 48 women, the MONET study found that neither weight nor BMI were influenced by FMP time and that percent fat mass was greater in the post-FMP years than it had been previously; however, but no change in percent fat was noted in the transitional phase prior to FMP.

Although each of these studies concluded that the MT did not influence body composition or weight, small samples, correspondingly few observed FMP dates, and — in one instance — long intervals between assessments constrained their ability to discover a nonlinear trajectory of body composition or weight with FMP time.

More frequently, investigators examined the relation between advancing menstrual pattern—based MT stage i. Five of these studies, including 2 from the initial years of SWAN, found that weight increased over time but was unrelated to evolving MT stage 13 — 16 , Limitations included few conversions from earlier to later MT stages and, in some cases, long spans between assessments 13 — 16 , Dissimilar to prior reports, the current analysis supports a strong, adverse influence of the MT on body composition that is manifest during the MT and then halts.

As reported by others, we observed weight gain starting in premenopause with a linear trajectory not inflected at the MT, but our body composition measures offer an explanatory insight, as described above.

SWAN also detects a cessation of weight gain in postmenopause except for postmenopausal Chinese women, whose weight not only stabilizes but declines , suggesting the advent of a new steady state and inferring a role for the end of the MT as one of its determinants.

Mounting evidence points to both estradiol E2 and follicle stimulating hormone FSH as regulators of energy balance; MT-related variations in each are plausible mechanisms of the results reported here 4 , 5.

The time course of the trajectories of body composition mirror E2 and FSH trajectories in relation to the FMP. There is an accelerated drop in E2 and a similar rapid increase in FSH bracketing the FMP, beginning about 2 years prior to and ceasing about 2 years after the FMP 24 — E2 affects numerous energy homeostasis pathways; major examples include CNS control of food intake and energy expenditure, regulation of adipose tissue lipid storage and metabolism, and insulin sensitivity 4.

Murine and rodent experimental manipulations e. Small cross-sectional and longitudinal observational studies find that resting energy expenditure REE is less in postmenopause than in premenopause 29 , In premenopausal women, pharmacological suppression of sex hormones by sustained administration of a gonadotropin releasing hormone agonist GnRH-a lowers REE; adding back transdermal E2 offsets the GnRH-a—induced decline in REE This same paradigm of pharmacological hormone suppression with and without the addition of transdermal E2 results in a loss of lean mass assessed by DXA only in the women who do not receive the E2 treatment Murine studies with a potentially novel FSH-blocking antibody demonstrate that, in ovarian-intact animals with unaltered serum E2 levels, FSH antibody reduces body fat but does not change body weight, similar to our human data The FSH antibody exerts several beneficial effects on energy balance, such as inducing the beiging of adipocytes conversion of white adipocytes to beige adipocytes, which are more metabolically active , a greater rate of thermogenesis, and activation of brown energy consuming adipocytes In our study, lean mass declined at the onset of the MT.

DXA lean mass measurement consists of total body water, muscle mass, and organ mass as noted in Methods, we excluded bone mass from the lean mass computation.

Therefore, decreasing lean mass could be due to diminution of any of these components. As reviewed by Stachenfeld, estrogen influences several physiological mechanisms that maintain water and salt balance Thus, an MT-related shift in fluid regulation could contribute to our observed reduction in lean mass.

There have been some investigations of the relation between menopause and muscle, but these have compared pre- vs. postmenopausal women or made inferences based on age rather than MT stage 35 , Nonetheless, these studies suggest plausible means by which the MT may diminish muscle mass, such as upregulation of skeletal muscle catabolism or lessened muscle response to anabolic stimuli e.

Declines in estrogen could underlie detrimental MT effects on muscle; the neuromuscular system is replete with α and β estrogen receptors, and when taken in early postmenopause, HT may preserve the muscle transcriptome and benefit muscle strength Progesterone can increase protein synthesis in women; therefore, persistently low progesterone levels could contribute to a decline in lean mass In men, androgens regulate lean mass, but androgen levels do not decline across the MT and are, therefore, unlikely to account for the a decrease in lean mass 38 , The menopause may also negatively influence muscle by indirect pathways — for example, by downregulating the anabolic IGF-1 pathway or by leading to a more preinflammatory milleu 40 , While increases in fat mass and decreases in lean mass were similar in Black and White women, findings in the 2 Asian groups were distinctive.

Our findings do not align with the few existing reports in Asian samples. On average, we found that Japanese SWAN participants, like White participants, lost lean mass during the MT, but unlike White participants, their fat mass and weight did not change during the MT.

This is in contrast to a cross-sectional survey of Japanese women aged 20—70 years that found postmenopause was associated not only with lower lean mass, but also with greater body fat In our study, during the postmenopausal interval, Chinese SWAN participants lost fat mass and body weight and gained lean mass proportion, which is in opposition to a prior single-site, cross-sectional SWAN analysis that reported lower lean mass and higher percent body fat in late peri- or postmenopausal Chinese participants We did not witness an effect of HT on body composition or weight measures, but HT use was infrequent and only occurred during postmenopause.

Thus, whether the use of HT lessens or prevents worsening of body composition during the transition from pre- to postmenopause, analogous to the GnRH-a with E2 add-back model, cannot be inferred from our analysis A limitation of this study is that we were unable to consider the effect of the MT on regional body composition and visceral fat at this time.

Owing to the complexity of the current analysis, we did not directly examine the relation between trajectories of sex steroids or gonadotropins and body composition and weight outcomes.

Subsequent investigations will remedy these limitations. Factors such as clothing worn and time of day may affect both accuracy and precision of anthropometric measures; standard SWAN protocols mitigated against these potential influences.

Ours is a community-based, but not a population-based, sample; therefore, results may not be generalizable to US Black, Chinese, Japanese, and White women.

Study strengths are several. First, we analyzed DXA-quantified body composition and measured weight in proximity, providing insight about how they are related.

We also benefitted by using time to and from FMP to capture the effect of the transition from pre- to postmenopause on body composition and weight; an FMP time-referenced analysis is a more discriminating assessment of progress through the transition that is an analysis based on clinical MT stages In summary, the MT is accompanied by accelerated gains in fat mass and simultaneous losses in lean mass; their joint rates of change result in no detectable acceleration in weight or BMI at the onset of the MT.

That an MT-related acceleration in weight or BMI is not observed, despite the high-velocity increase in fat mass, is concordant with the growing appreciation that, while BMI is a well-established, strong composite indicator of cardiometabolic risk, it is a less strong index of adiposity and particular aspects of adiposity such as the location of fat 44 , As a result, BMI is a less useful indicator of cardiometabolic risk in older women BMI is body weight normalized to the square of height.

However, inputs to weight include fat mass and lean mass, each of which may vary differentially and may variably contribute to specific aspects of cardiometabolic and other health risks This description of how the MT affects individual compartments of body composition lays the groundwork for investigating how MT-related body composition changes may affect the health of postmenopausal women and how relative weight and body composition may make distinctive contributions to a range of physiological outcomes.

Study sample. SWAN is a multisite, community-based, longitudinal cohort study The 7 SWAN clinical sites Boston, Massachusetts, USA; Chicago, Illinois, USA; Detroit, Michigan, USA; Pittsburgh, Pennsylvania, USA; Los Angeles, California, USA; Newark, New Jersey, USA: and Oakland, California, USA enrolled participants.

All sites enrolled White women. Boston, Chicago, Detroit, and Pittsburgh enrolled Black women and the remaining 3 sites enrolled Japanese, Hispanic, and Chinese women, respectively. The baseline visit visit 00 occurred in —, and the final study visit included in this analysis visit 13 occurred during — The Chicago and Newark sites did not assess body composition using Hologic DXA instruments; thus, participants from the remaining 5 sites were eligible for the SWAN Bone Density and Body Composition Cohort.

Figure 3 illustrates the current analysis sample derivation. Derivation of the analysis sample for analysis of body composition and weight in relation to the FMP.

This analysis considers 6 outcomes: 4 DXA-acquired body composition measures, measured weight, and BMI. Body composition variables omit the head from the calculation.

The lean mass estimate used here is exclusive of bone mass to avoid contamination by unremovable metal artifacts. We measured body composition at each SWAN visit using Hologic instruments Hologic Inc.

Three sites began SWAN with Hologic QDR A models; 2 of these transitioned to Discovery models during follow-up. Two sites began with QDR models and upgraded to QDR A models during follow-up. Sites that changed densitometers scanned volunteers on their old and new machines for cross-calibration.

The Supplemental Material, Setions B and C presents a detailed description of hardware, software, coefficients of variation, and calibrations. DXA procedures require exclusion of the left arm when the participant is too large to allow both upper extremities to rest on the scan bed while maintaining sufficient separation to define soft tissue regions.

Employing data from women who had both arms measured, we used right arm values to impute left arm values, accounting for hand dominance if unknown, assumed right-handedness. For left-handed participants, raw right arm and left arm values were similar; therefore, we substituted their right arm values for left.

A body composition machine can estimate what yours is. To work out a healthy rate of weight loss, calculate your Total Daily Energy Expenditure TDEE from your BMR.

The formula uses your BMR and activity level to estimate how much energy you need to maintain your current weight. To lose weight, you just need to eat below this figure. Typically, you will see recommendations to drop below your TDEE by calories. This is based on the fact that grams of fat is represented by 3, calories, and therefore if you eat calories less every day for a week, you will lose about grams each week.

General advice is that losing more than this puts you at risk of slowing down your metabolism, losing muscle, and nutritional deficiencies 3.

However, every person is different and it is important that you speak to your doctor if you have any concerns about your body and what a healthy rate of weight loss is for you. If your priority is to build muscle, you need to ensure you eat more than your TDEE.

In order to maximise skeletal muscle mass gain and minimise fat mass gain, the increase should be made up of protein rich foods and carbohydrates. It is important that you consume a balanced diet — studies have suggested that there is no benefit to consuming more than 0.

Moreover, you still need all the good energy and minerals that come from wholegrains and plenty of vegetables. Building muscle is not a fast process. For a variety of reasons, older adults eat less as they age, and it is easy for them to become undernourished.

Careful monitoring of BMI and body composition can prevent malnutrition and simultaneously provide information about the effectiveness of maintenance, reduction, and weight gain programs.

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