Methylation and Expression of Retinoblastoma and Transforming Growth Factor-β1 Genes in Epstein-Barr Virus-Associated and -Negative Gastric Carcinomas
Hindawi Publishing CorporationCopyright Hindawi Publishing Corporation

Xia Liu
Department of Medical Microbiology
Qingdao University Medical College
38 Dengzhou Road266021QingdaoChina

Xiuming Tang
Department of Central Laboratory
The Affiliated Hospital of Qingdao University Medical College
19 Jiangsu Road266003QingdaoChina

Shaoyan Zhang
Department of Laboratory
The Affiliated Hospital of Qingdao University Medical College
Qingdao University
19 Jiangsu Road266003QingdaoChina

Yun Wang
Department of Medical Microbiology
Qingdao University Medical College
38 Dengzhou Road266021QingdaoChina

Xiaofeng Wang
Chengquan Zhao
Department of Medical Microbiology
Qingdao University Medical College
38 Dengzhou Road266021QingdaoChina

Department of Pathology
University of Pittsburgh Medical Center
15213PittsburghPAUSA

Bing Luo firstname.lastname@example.com
Department of Medical Microbiology
Qingdao University Medical College
38 Dengzhou Road266021QingdaoChina

Methylation and Expression of Retinoblastoma and Transforming Growth Factor-β1 Genes in Epstein-Barr Virus-Associated and -Negative Gastric Carcinomas

Gastroenterology Research and Practice
Hindawi Publishing Corporation201210.1155/2012/906017Received 25 May 2012; Revised 8 August 2012; Accepted 13 August 2012Research Article Correspondence should be addressed to Bing Luo, Academic Editor: A. Castells
Background. Retinoblastoma (RB) and transforming growth factor-β1 (TGF-β1) are important tumor-related factors. Methods. A series of 30 EBV-associated gastric carcinoma (EBVaGC) and 38 matched EBV-negative gastric carcinoma (EBVnGC) tissues were examined for the promoter methylation of RB by methylation-specific PCR (MSP) method. The expression of RB and TGF-β1 in gastric carcinoma tissues was detected by immunohistochemistry. Results. The methylation rate of RB gene in EBVaGC and EBVnGC was 80.0% (24/30) and 50.0% (19/38), respectively. The difference of RB methylation rate between EBVaGC and EBVnGC was significant (χ 2 = 6.490, P = 0.011). There was no significant difference for RB expression between EBVaGC (43.3%, 13/30) and EBVnGC (63.2%, 24/38), and also for TGF-β1 between EBVaGC (56.7%, 17/30) and EBVnGC (63.2%, 24/38). RB methylation was not reversely correlated with RB expression in gastric carcinoma tissues (χ 2 = 2.943, P = 0.086, r = 0.208). RB methylation, loss expression of RB, and TGF-β1 expression were significantly associated with tumor invasion and lymph node metastasis (P < 0.05), but was not associated with sex, age, histological subtype (differentiation status) and tumor location. Conclusions. Methylation of RB is a common event in gastric carcinomas and EBV induces methylation of RB in EBVaGC, which may contribute to the development of gastric carcinomas. EBV has no significant effect on induction of TGF-β1 expression. Detection of RB methylation, RB expression, and TGF-β1 expression may be helpful to judge the status of tumor invasion and lymph node metastasis in gastric carcinomas.

Introduction

Gastric carcinoma is the second leading cause of cancerrelated death worldwide [1]. Epstein-Barr virus (EBV) is a tumor-related herpes virus associated with the transformation of various types of cells, such as lymphoid, dendritic, smooth muscle, and epithelial cells [2]. EBVassociated gastric carcinoma (EBVaGC) is characterized by the monoclonal growth of EBV-infected epithelial cells, and the entity was recognized by Imai in 1994 [3]. EBVaGC is distributed worldwide with an annual incidence of more than 90,000 patients (10% of total gastric carcinoma (GC)) [4]. Following infection, EBV remains in a latent state in EBVaGC, which is classified as latency I. Compared with EBV-negative gastric carcinoma (EBVnGC), EBVaGC has unique clinical and pathological features, such as a younger age of incidence, high incidence in men than in women, and more diffuse than intestinal types [5][6][7], suggestive of a particular oncogenic mechanism of EBVaGC.

Epigenetic alterations, including methylation of CpG dinucletides in promoters and changes in chromatin structure, can affect gene expression without modifying the underlying in genetic sequences. Aberrant methylation of promoters in tumor-related genes is now regarded as one of the major mechanisms in the development of gastric carcinoma [8]. Tumor-related genes p16, p14, E-cadherin, PTEN (phosphatase and tensin homolog deleted on chromosome ten), RASSF1A (Ras association domain family 1A), GSTP1 (Glutathione S-transferase pi 1), MGMT (O (6)-methylguanine-DNA-methyltransferase), and MINT2 (Munc18-1-interacting protein 2) are hypermethylated in EBVaGC [9][10][11], suggesting that EBV-related aberrant methylation may play an important role in development of EBVaGC.

Retinoblastoma (RB) and transforming growth factor-β1 (TGF-β1) are important regulatory factors in cell growth and differentiation, whose abnormal transcription or expression are closely associated with tumor occurrence and development. RB was the first successfully cloned human tumor suppressor gene (TSG). Its inactivation may result in cell proliferation leading to tumorigenesis [12]. TGF-β1 is a multifunctional cytokine and triggers an intracellular signal transduction protein to regulate numerous developmental and homoeostatic processes via regulation of gene induction. It plays a dual regulatory role in cell proliferation and differentiation. In the early stage of cancer, TGF-β1 can inhibit cell proliferation through arrest in the G1 phase and be regarded as a tumor suppressor; in the late stages, TGF-β1 becomes a tumor promoting factor by stimulating angiogenesis, cell spread, immune suppression, and synthesis of extracellular matrix [13][14][15][16]. It has been reported that EBV latent membrane protein 1 (LMP1) has a resistant to the TGF-β1-mediated growth inhibition in EBV-positive gastric carcinoma cell lines (GT38 and GT39) and indicated that TGF-β1 may be a key factor for EBV reactivation and selective growth of EBV-infected epithelial cells in vivo [17,18]. However, the LMP1 expression is absent in EBVaGC tissues [19]. The identified role of TGF-β1 in EBVaGC has not been understood well and needs further research. The absence of RB expression and overexpression of TGF-β1 have been found in gastric carcinomas [20,21], and the mutations and methylation of RB gene in gastric carcinomas were also reported in the literature [22,23]. Mukherjee et al. [24] found TGF-β1 treatment in late G(1) acutely blocks S-phase entry, this acute block by requiring the function of RB and loss of RB abrogates late-G(1) arrest by TGF-β1, suggesting a novel role for RB in mediating this effect of TGF-β1 late-G(1) arrest through direct interaction with and control of the MCM helicase. However, there is no report about the expression and promoter methylation status of RB and TGF-β1 in EBVaGC and EBVnGC to our knowledge. In this study, we examined RB methylation status, RB and TGF-β1 protein expression in EBVaGC and matched EBVnGC. The aim of the study is to understand the relationship among EBV, RB and TGF-β1 and their role in gastric carcinoma tumorgenesis.

Materials and Methods

Patients and Tissue Samples.

Fresh and paraffinembedded gastric carcinoma tissues were obtained from 1678 gastric carcinoma patients in Shangdong Province, China from 2001 to 2009. The positivity of EBV in GC tissues was determined by EBV-encoded small RNA 1 in situ hybridization, as described previously [25]. The clinical features (gender, age, pathologic grade, location, invasion and lymph node metastasis) matched 30 EBVaGC and 38 EBVnGC samples were chosen for study. The study was approved by the Medical Ethics Committee at the Medical College of Qingdao University, China, and informed consent was received from all patients.

2.2. DNA Extraction. DNA was extracted from fresh tumor tissues using the standard method with proteinase K digestion and phenol-chloroform purification. The QIAamp DNAFFPE Tissue kit (QIAGEN GmbH, Hilden, Germany) was used to extract the DNA from paraffin-embedded tumor tissues.

Immunohistochemistry (IHC).

Paraffin sections were deparaffinized and hydrated as per routine. Rabbit antihuman polyclonal antibody TGF-β1 and mouse antihuman monoclonal antibody RB (ZSGB-Bio) were diluted to 1 : 50. The reagents (PV9000 and DAB) were obtained from ZSGB-Bio and staining was performed as per protocol. PBS (phosphate buffer saline) was used in replacement of primary antibody as a blank control. The section was considered as expressing the protein if cellular staining ≥5%, following the methods described previously [26,27].  [28]. DNA was desalted and purified using the QIAEX Gel Extraction system (QIAGEN, Cat. no.20021). DNA was then treated with 0.3 mol/L NaOH at 37 • C for 15 minutes and precipitated with 3 mol/L ammonium acetate (pH 7.0) and 1 mol/L sodium acetate (pH 5.2). Recovered DNA was dissolved in 100 μL of TE buffer (pH 8.0) and stored at −20 • C.

RB promoter methylation status was determined using MSP. In this method, bisulfite treatment converts unmethylated cytosine to uracil, but does not affect the methylated cytosine. Thus, PCR primers can be designed that anneal selectively to methylated or unmethylated DNA after bisulfite conversion. The sequences of the unmethylated DNA and methylated DNA-specific primers are listed in Table 1. The primer UF/UR pair was designed specifically for amplification of the bisulfite-converted unmethylated promoter, while the MF/MR primer pair was designed specifically for the amplification of the bisulfite-converted methylated promoter. MSP results determined whether the samples are methylated or unmethylated. If there is M primers amplified band, the sample was considered to be in the methylation status. One microliter of bisulfite-treated DNA (around 25 ng) was amplified with 1.5 mmol/L MgCl 2 and

Results

Comparison of Clinicopathological Data between EBVaGC and EBVnGC

Patients. 102 of 1678 (6.1%) cases of gastric carcinoma were EBV positive. 30 EBVaGC and 38 EBVnGC tumor tissues with matching clinical parameters were chosen for methylation detection. The clinical and pathological data are listed in Table 2. The two kinds of gastric carcinomas were similar in gender, age, pathologic grade, location, invasion, and lymph node metastasis.

The Promoter Methylation Status of RB Gene in EBVaGC and EBVnGC.

Promoter methylation of the RB gene was detected by MSP (Figure 1(a)). In total, 43 The association of clinicopathological parameters of 68 cases with RB gene methylation status was studied. There was no relationship of RB gene methylation status with patient age, gender, pathologic types, and tumor location. However, the methylation status was associated with the depth of tumor invasion (P = 0.036) and lymph node metastasis (P = 0.012), (Table 3).

The Promoter Methylation Status of RB Gene in GC

and Corresponding Adjacent Normal Gastric Tissues. The promoter methylation of RB gene was detected in EBVaGC and EBVnGC corresponding adjacent normal gastric tissues (Figure 1(b)).   RB protein expression cases in 43 RB gene methylated gastric carcinoma (53.5%), which was higher than in RB gene unmethylated gastric carcinoma (32.0%, 8/25), but without reverse correlation (P = 0.09, r = 0.21), ( Table 5).

The association between RB expression and clinicopathological parameters is shown in Table 6. There was no relationship between RB protein expression and patients' age, gender, pathological grade, and tumor location, but it was related with the depth of tumor invasion (P = 0.04) and lymph node metastasis (P = 0.02).

The association between TGF-β1 expression and clinicopathological parameters is shown in Table 6. There was   no relationship between TGF-β1 protein expression and patients' age, gender, pathological types, and tumor location, but there was positive association between TGF-β1 protein expression and the depth of tumor invasion (P = 0.02) and lymph node metastasis (P = 0.002).

Discussion

In this study, the percent of EBVaGC with positive methylation bands by MSP for RB was significantly higher than that of EBVnGC, indicating that EBV may induce RB promoter methylation during infection. Previous studies showed that EBVaGC had higher methylation frequency and promoter CpGI methylation density than EBVnGC in some TSGs, such as p16, E-cadherin and p73, and the methylation status was reverse correlated with protein expression [4,10,29]. These results indicate that methylation and silence of TSGs induced by EBV may be an important oncogenic mechanism for the development of EBVaGC. Only a few studies detected the methylation of RB in gastric carcinomas. Zhao et al. [30] found that the percent of positive methylation bands for RB gene was 44.6% (45/101), similar to our study of 38 EBVnGC (50%), but less than that of 30 EBVaGC cases (80%), which provides further support that EBV induces RB gene methylation in EBVaGC. Promoter CpG island methylation is considered an important mechanism of TSG inactivation. In the present study, 23 of 43 (53.5%) methylated gastric carcinoma tissues lost RB protein expression, which was higher than that in unmethylated gastric carcinoma tissues (32.0%, 8/25), but RB promoter methylation was not reversely correlated with RB protein expression (P = 0.086). This phenomenon was also found between p16INK4 gene methylation status and expression in meningiomas by Tse et al. [31]. The possible explanations include: (1) gene methylation in gastric carcinoma tissue is heterogeneous; (2) gene methylation may occur in only one allele of cancer cells, while the other allele remains unmethylated. The above reasons may also explain the existence of methylated and unmethylated gene 6 Gastroenterology Research and Practice bands by MSP. Increasing of CpG island methylation density is a dynamic process, and only the methylation density increases to a certain extent, it results in the complete loss of the expression. The RB promotor methylation could result the decrease or loss of protein expression. Thus, lacking reverse correlation between RB promotor methylation and protein expression was not contradictory. Because of the limitation of major disadvantage of MSP, the methylation status of single CpG site in primer binding sequences is not be detected [32]. The correlation between RB promoter methylation dynamic change and protein expression need further study. These reasons above can also be used to explain why there wasn't a significant difference in RB protein expression between EBVaGC and EBVnGC, even though RB promoter methylation of EBVaGC was significantly higher than EBVnGC. If the RB gene promoter methylation and its protein expression were negatively correlated, RB protein expression in EBVaGC should have been significantly lower than that in EBVnGC. In this study, the percent of EBVaGC and EBVnGC that were positive by IHC for RB were 43.3% and 63.2%, respectively. Although no significant difference was found of the positive rate of RB protein expression between EBVaGC and EBVnGC, the relatively lower expression rate in EBVaGC also suggests that EBVinduced RB promoter methylation could lead to inhibition of RB protein expression to some extent. Moreover, the promoter methylation of RB gene was also detected in GC and corresponding adjacent normal gastric tissues and the difference was significant, which confirmed that RB promoter methylation is involved with the development of GC.

Similar to the result of RB protein expression, the positive rate of TGF-β1 protein expression was 56.7% (17/30) and 63.2% (24/38) in EBVaGC and EBVnGC, respectively, without significant difference (P = 0.404), suggesting that EBV is not related to the TGF-β1 expression in EBVaGC. Kim et al. [33] examined the association of EBV with RB and p53 protein expression in classic Hodgkin lymphoma and found that EBV wasn't associated with RB and p53 protein expression. Xu et al. [34] found TGF-β1 level in the serum of nasopharyngeal cancer patients was significantly higher than that in normal persons, and also the advanced stage was higher than the early stage, and recurrent tumors was higher than primary tumors, which indicating that serum TGF-β1 can be used for diagnosis and judgment for prognosis of NPC, and EBV infection can induce the synthesis and release of TGF-β1. This result was different from our result of TGF-β1 in EBVaGC.

Previous studies showed that TGF-β1 expression rate and expression level were higher in gastric carcinoma tissues than that in normal tissues, and the TGF-β1 expression were associated with gastric invasion, metastases, and prognosis [35][36][37]. In the advanced cancer, TGF-β1 can provide the microenvironment suitable for tumor growth, invasion, and metastases by stimulating angiogenesis, cell spread, immune suppression, and synthesis of extracellular matrix. In gastric carcinoma, RB protein loss was also found to be associated with metastases and prognosis [38][39][40][41]. The RB protein expression rate was 40% ∼ 90% [38-40, 42, 43] and TGF-β1 protein expression rate was 22.8% ∼ 71% [35][36][37]44] in previous studies. In the present study, RB protein loss and TGF-β1 protein wasn't associated with patient age, gender, 7 pathologic types, and tumor location, but associated with the depth of tumor invasion and lymph node metastasis. At the same time, we also confirmed that RB promoter methylation was associated with tumor invasion and lymph node metastasis, indicating that RB promoter methylation, RB and TGF-β1 protein expression can be as clinical reference index for judgement of gastric carcinoma invasion and metastasis.

Conclusion

Our study showed that Aberrant RB promoter methylation was common in gastric carcinoma. EBV could induce RB gene methylation and affect the gene expression in EBVaGC development. EBV has no significant effect on TGF-β1 expression.

Abbreviations

GC:

Tumor suppressor gene RB:

2. 4 .
4Bisulfite Treatment of Genomic DNA and Methylation-Specific PCR (MSP). 5 μg DNA was denatured in 33.3 μL of 0.3 mol/L NaOH at 37 • C for 15 minutes. Denatured DNA was mixed directly with 333 μL of bisulfite solution and treated in darkness. The bisulfite solution was prepared as either 2.4 mol/L sodium metabisulfite (pH 5.0-5.2) (Sigma S-1516, St. Louis, MO, USA)/0.5 mmol/L hydroquinone (Sigma H-7148) for a 4-hour treatment

Figure 1 :
1RB promoter methylation in EBVaGC, EBVnGC, and matched paracarcinoma tissues. (a) Representative RB promoter methylation in EBVaGC and EBVnGC by MSP. U, PCR product from the MSP assay using primers specific for the unmethylated allele; M, PCR product from the MSP assay using primers specific for the methylated allele. (b) Representative RB MSP assay results for matched paracarcinoma tissues.

Figure 2 :
2The protein expression of RB and TGF-β1 by immunohistochemistry (magnification ×100). (a) Positive immunohistochemistry result of RB in paraffin section. Expression of RB was found in nuclei of gastric carcinoma cells. (b) Positive immunohistochemistry result of TGF-β1 in paraffin section. Expression of TGF-β1 was found in cytoplasm of gastric carcinoma cells. (c) Negative immunohistochemistry result of RB in paraffin section. (d) Negative immunohistochemistry result of TGF-β1 in paraffin section.

Table 1 :
1List of primers used in MSP. Statistical Analysis. RB promoter methylation status, RB expression and TGF-β1 expression between EBVaGC and EBVnGC was compared using the Chi-square test. The correlation between promoter methylation and the protein expression was analyzed by Paired fourfold table Chi-square test. The association of clinical features with RB promoter methylation, RB expression, and TGF-β1 expression was compared by chi-square test. P < 0.05 was considered to be statistically significant.Primers
Sequence
Product size (bp)
Annealing temp (0 • C)
Genomic position
RBMF
5 GGGAGTTTCGCGGACGTGAC3
163
60
−61 to 102
RBMR
5 ACGTCGAAACACGCCCCG3
RBUF
5 GGGAGTTTTGTGGATGTGAT3
163
58
−61 to 102
RBUR
5 ACATCAAAACACACCCCA3

0.2 mmol/L dNTP in a 25 μL reaction volume. Primers
were used at a final concentration of 0.4 mmol/L each.
The PCR involved an initial denaturation at 94 • C for 10
minutes, followed by 40 cycles consisting of 94 • C for 30
seconds, predetermined optimal annealing temperature for
30 seconds, 72 • C for 30 seconds, and a final extension at
72 • C for 5 minutes. Eight microliters of PCR product were
analyzed on a 2.0% agarose gel. Water was used as a negative
control.

2.5.

Table 2 :
2Comparison of clinicopathological data between EBVaGC and EBVnGC patients.EBVaGC
(n = 30)

EBVnGC
(n = 38)
χ 2
P

The correlation of RB protein expression with RB promoter methylation was studied. There were 23 negativeThe percent of positive methylation bands by
MSP for RB in gastric carcinoma and corresponding adjacent
normal gastric tissues was 63.2% (43/68) and 39.7% (27/68);
the difference was significant (P = 0.006).

3.4. The Protein Expression of RB and TGF-β1. RB and
TGF-β1 protein expression was detected by IHC, shown in
Figures 2(a) and 2(b). The percent of EBVaGC that were
positive by IHC for RB was 43.3% (13/30), lower than in
EBVnGC (63.2%, 24/38), but not significantly different (P =
0.103). There was not obvious difference of TGF-β1 protein
expression between EBVaGC (56.7%, 17/30) and EBVnGC
(63.2%, 24/38) (P = 0.587) (Table 4).
EBVaGC

EBVnGC

Rb m

Rb u

Rb m

Rb u

GC86
GC89
GC90
GC92
GC93
GC94
GC95
GC96
GC97
GC98

Y3A
Y4A
Y6A
Y9A
Y11A
Y12A
Y14A
Y15A
Y16A
Y17A

(a)

Rb m

Rb u

Rb m

Rb u

GC86
GC89
GC90
GC92
GC93
GC94
GC95
GC96
GC97
GC98

Y3A
Y4A
Y6A
Y9A
Y11A
Y12A
Y14A
Y15A
Y16A
Y17A

EBVaGC matched

Para-carcinoma

Para-carcinoma

EBVnGC matched

(b)

Table 3 :
3Correlation of methylation status of RB gene with clinicopathological data of gastric carcinoma patients.n
Methylated (n)
U n m e t h y l a t e d( n)
χ 2
P

Table 4 :
4Comparisons of the expression of RB and TGF-β1 between EBVaGC and EBVnGC.n
RB expression
TGF-β1 expression
Positive
Negative
Positive
Negative
EBVaGC 30
13
17
17
13
EBVnGC 38
24
14
24
14
χ 2
2.656
0.295
P
0.103
0.587

Table 5 :
5Correlation of methylation status of RB gene with its protein expression.Methylation status
Protein expression
Total
Positive
Negative
Methylated
20
23
43
Unmethylated
17
8
25
Total
37
31
68

Table 6 :
6Correlation of expression of RB and TGF-β1 protein with clinicopathological data of gastric carcinoma patients.n
RB
TGF-β1
Expression (n) Absent (n) χ 2
P Expression (n) Absent (n) χ 2
P

AcknowledgmentsThis research was supported by the Grant from National Natural Science Foundation of China (NSFC 30970157). The authors thank Stacey Barron (University of Pittsburgh, Pittsburgh, PA, USA) for her helpful review of the paper.Conflict of InterestsNone of the authors has any conflicts of interests.
The future of gastric cancer prevention. P Correa, M B Piazuelo, M C Camargo, Gastric Cancer. 71P. Correa, M. B. Piazuelo, and M. C. Camargo, "The future of gastric cancer prevention," Gastric Cancer, vol. 7, no. 1, pp. 9-16, 2004.

Epstein-Barr virus and gastric carcinoma-viral carcinogenesis through epigenetic mechanisms. H Uozaki, M Fukayama, International Journal of Clinical and Experimental Pathology. 13H. Uozaki and M. Fukayama, "Epstein-Barr virus and gastric carcinoma-viral carcinogenesis through epigenetic mech- anisms," International Journal of Clinical and Experimental Pathology, vol. 1, no. 3, pp. 198-216, 2008.

Gastric carcinoma: monoclonal epithelial malignant cells expressing Epstein-Barr virus latent infection protein. S Imai, S Koizumi, M Sugiura, Proceedings of the National Academy of Sciences of the United States of America. the National Academy of Sciences of the United States of America91S. Imai, S. Koizumi, M. Sugiura et al., "Gastric carcinoma: monoclonal epithelial malignant cells expressing Epstein-Barr virus latent infection protein," Proceedings of the National Academy of Sciences of the United States of America, vol. 91, no. 19, pp. 9131-9135, 1994.

p73 gene promoter methylation in Epstein-Barr virus-associated gastric carcinoma. T Ushiku, J M Chong, H Uozaki, International Journal of Cancer. 1201T. Ushiku, J. M. Chong, H. Uozaki et al., "p73 gene pro- moter methylation in Epstein-Barr virus-associated gastric carcinoma," International Journal of Cancer, vol. 120, no. 1, pp. 60-66, 2007.

Epstein-Barr virus associated gastric carcinoma: epidemiological and clinicopathological features. S Akiba, C Koriyama, R Herrera-Goepfert, Y Eizuru, Cancer Science. 992S. Akiba, C. Koriyama, R. Herrera-Goepfert, and Y. Eizuru, "Epstein-Barr virus associated gastric carcinoma: epidemio- logical and clinicopathological features," Cancer Science, vol. 99, no. 2, pp. 195-201, 2008.

Clinicopathological and molecular characteristics of Epstein-Barr virus-associated gastric carcinoma: a metaanalysis. J H Lee, S H Kim, S H Han, J S An, E S Lee, Y S Kim, Journal of Gastroenterology and Hepatology. 243J. H. Lee, S. H. Kim, S. H. Han, J. S. An, E. S. Lee, and Y. S. Kim, "Clinicopathological and molecular characteristics of Epstein-Barr virus-associated gastric carcinoma: a meta- analysis," Journal of Gastroenterology and Hepatology, vol. 24, no. 3, pp. 354-365, 2009.

Epstein-Barr virus and gastric carcinoma: virus-host interactions leading to carcinoma. M Fukayama, R Hino, H Uozaki, Cancer Science. 999M. Fukayama, R. Hino, and H. Uozaki, "Epstein-Barr virus and gastric carcinoma: virus-host interactions leading to carcinoma," Cancer Science, vol. 99, no. 9, pp. 1726-1733, 2008.

Cancer epigenetics. R Taby, J P Issa, Cancer Journal for Clinicians. 606R. Taby and J. P. Issa, "Cancer epigenetics," Cancer Journal for Clinicians, vol. 60, no. 6, pp. 376-392, 2010.

High-density methylation of p14ARF and P16INK4A in Epstein-Barr virusassociated gastric carcinoma. K Sakuma, J M Chong, M Sudo, International Journal of Cancer. 1122K. Sakuma, J. M. Chong, M. Sudo et al., "High-density methylation of p14ARF and P16INK4A in Epstein-Barr virus- associated gastric carcinoma," International Journal of Cancer, vol. 112, no. 2, pp. 273-278, 2004.

Promoter hypermethylation of E-cadherin and its abnormal expression in Epstein-Barr virus-associated gastric carcinoma. M Sudo, J M Chong, K Sakuma, International Journal of Cancer. 1092M. Sudo, J. M. Chong, K. Sakuma et al., "Promoter hyper- methylation of E-cadherin and its abnormal expression in Epstein-Barr virus-associated gastric carcinoma," Interna- tional Journal of Cancer, vol. 109, no. 2, pp. 194-199, 2004.

Epstein-Barr viruspositive gastric carcinoma demonstrates frequent aberrant methylation of multiple genes and constitutes CpG island methylator phenotype-positive gastric carcinoma. G H Kang, S Lee, W H Kim, American Journal of Pathology. 1603G. H. Kang, S. Lee, W. H. Kim et al., "Epstein-Barr virus- positive gastric carcinoma demonstrates frequent aberrant methylation of multiple genes and constitutes CpG island methylator phenotype-positive gastric carcinoma," American Journal of Pathology, vol. 160, no. 3, pp. 787-794, 2002.

The retinoblastoma gene: role in cell cycle control and cell differentiation. K G Wiman, FASEB Journal. 710K. G. Wiman, "The retinoblastoma gene: role in cell cycle control and cell differentiation," FASEB Journal, vol. 7, no. 10, pp. 841-845, 1993.

TGF-β signaling in cancer-a double-edged sword. R J Akhurst, R Derynck, Trends in Cell Biology. 1111R. J. Akhurst and R. Derynck, "TGF-β signaling in cancer-a double-edged sword," Trends in Cell Biology, vol. 11, no. 11, pp. S44-S51, 2001.

Signal transduction by the TGF-β superfamily. L Attisano, J L Wrana, Science. 2965573L. Attisano and J. L. Wrana, "Signal transduction by the TGF-β superfamily," Science, vol. 296, no. 5573, pp. 1646-1647, 2002.

Integration of the TGF-β pathway into the cellular signalling network. M Lutz, P Knaus, Cellular Signalling. 1412M. Lutz and P. Knaus, "Integration of the TGF-β pathway into the cellular signalling network," Cellular Signalling, vol. 14, no. 12, pp. 977-988, 2002.

Cellular growth inhibition by TGF-beta1 involves IRS proteins. S S Huang, S M Leal, C L Chen, I H Liu, J S Huang, FEBS Letters. 5651-3S. S. Huang, S. M. Leal, C. L. Chen, I. H. Liu, and J. S. Huang, "Cellular growth inhibition by TGF-beta1 involves IRS proteins," FEBS Letters, vol. 565, no. 1-3, pp. 117-121, 2004.

A mechanism in epstein-barr virus oncogenesis: inhibition of transforming growth factor-β1-mediated induction of MAPK/p21 by LMP1. M Fukuda, W Kurosaki, K Yanagihara, H Kuratsune, T Sairenji, Virology. 3022M. Fukuda, W. Kurosaki, K. Yanagihara, H. Kuratsune, and T. Sairenji, "A mechanism in epstein-barr virus oncogenesis: inhibition of transforming growth factor-β1-mediated induc- tion of MAPK/p21 by LMP1," Virology, vol. 302, no. 2, pp. 310-320, 2002.

Effect of transforming growth factor-β1 on the cell growth and Epstein-Barr virus reactivation in EBV-infected epithelial cell lines. M Fukuda, K Ikuta, K Yanagihara, Virology. 2881M. Fukuda, K. Ikuta, K. Yanagihara et al., "Effect of transform- ing growth factor-β1 on the cell growth and Epstein-Barr virus reactivation in EBV-infected epithelial cell lines," Virology, vol. 288, no. 1, pp. 109-118, 2001.

Gastric carcinoma: monoclonal epithelial malignant cells expressing Epstein-Barr virus latent infection protein. S Imai, S Koizumi, M Sugiura, Proceedings of the National Academy of Sciences of the United States of America. the National Academy of Sciences of the United States of America91S. Imai, S. Koizumi, M. Sugiura et al., "Gastric carcinoma: monoclonal epithelial malignant cells expressing Epstein-Barr virus latent infection protein," Proceedings of the National Academy of Sciences of the United States of America, vol. 91, no. 19, pp. 9131-9135, 1994.

Rb family proteins in gastric cancer. L Cito, F Pentimalli, I Forte, E Mattioli, A Giordano, Oncology Reports. 246L. Cito, F. Pentimalli, I. Forte, E. Mattioli, and A. Giordano, "Rb family proteins in gastric cancer," Oncology Reports, vol. 24, no. 6, pp. 1411-1418, 2010.

Relation between transforming growth factor-beta1 expression, its receptor and clinicopathological factors and survival in HER2-negative gastric cancers. J Ananiev, M Gulubova, G Tchernev, Wiener Klinische Wochenschrift. 12321-22J. Ananiev, M. Gulubova, G. Tchernev et al., "Relation between transforming growth factor-beta1 expression, its receptor and clinicopathological factors and survival in HER2-negative gastric cancers," Wiener Klinische Wochenschrift, vol. 123, no. 21-22, pp. 668-673, 2011.

. Gastroenterology Research and Practice. Gastroenterology Research and Practice

Epstein-Barr-Virus-associated gastric cancer in Russia. S A Galetsky, V V Tsvetnov, C E Land, International Journal of Cancer. 736S. A. Galetsky, V. V. Tsvetnov, C. E. Land et al., "Epstein- Barr-Virus-associated gastric cancer in Russia," International Journal of Cancer, vol. 73, no. 6, pp. 786-789, 1997.

Clinicopathologic characteristics of Epstein-Barr virusincorporated gastric cancers in Korea. M S Chang, H S Lee, C W Kim, Y I Kim, W H Kim, Pathology Research and Practice. 1976M. S. Chang, H. S. Lee, C. W. Kim, Y. I. Kim, and W. H. Kim, "Clinicopathologic characteristics of Epstein-Barr virus- incorporated gastric cancers in Korea," Pathology Research and Practice, vol. 197, no. 6, pp. 395-400, 2001.

Cell cycle arrest by transforming growth factor β1 near G 1/S is mediated by acute abrogation of prereplication complex activation involving an Rb-MCM interaction. P Mukherjee, S L Winter, M G Alexandrow, Molecular and Cellular Biology. 303P. Mukherjee, S. L. Winter, and M. G. Alexandrow, "Cell cycle arrest by transforming growth factor β1 near G 1/S is mediated by acute abrogation of prereplication complex activation involving an Rb-MCM interaction," Molecular and Cellular Biology, vol. 30, no. 3, pp. 845-856, 2010.

Carboxylterminal sequence variation of latent membrane protein 1 gene in Epstein-Barr virus-associated gastric carcinomas from eastern China and Japan. Y Wang, K Kanai, Y Satoh, B Luo, T Sairenji, Intervirology. 503Y. Wang, K. Kanai, Y. Satoh, B. Luo, and T. Sairenji, "Carboxyl- terminal sequence variation of latent membrane protein 1 gene in Epstein-Barr virus-associated gastric carcinomas from eastern China and Japan," Intervirology, vol. 50, no. 3, pp. 229- 236, 2007.

Clinical significance of altered nm23-H1, EGFR, RB and p53 expression in bilharzial bladder cancer. H M Khaled, A A Bahnassy, A A Raafat, A R N Zekri, M S Madboul, N M Mokhtar, BMC Cancer. 932H. M. Khaled, A. A. Bahnassy, A. A. Raafat, A. R. N. Zekri, M. S. Madboul, and N. M. Mokhtar, "Clinical significance of altered nm23-H1, EGFR, RB and p53 expression in bilharzial bladder cancer," BMC Cancer, vol. 9, p. 32, 2009.

The prognostic impact of TGF-β1, fascin, NF-κb and PKC-ζ expression in soft tissue sarcomas. A Valkov, S W Sorbye, T K Kilvaer, ID e17507PLoS ONE. 63A. Valkov, S. W. Sorbye, T. K. Kilvaer et al., "The prognostic impact of TGF-β1, fascin, NF-κb and PKC-ζ expression in soft tissue sarcomas," PLoS ONE, vol. 6, no. 3, Article ID e17507, 2011.

Defective de novo methylation of viral and cellular DNA sequences in ICF syndrome cells. Q Tao, H Huang, T M Geiman, Human Molecular Genetics. 1118Q. Tao, H. Huang, T. M. Geiman et al., "Defective de novo methylation of viral and cellular DNA sequences in ICF syndrome cells," Human Molecular Genetics, vol. 11, no. 18, pp. 2091-2102, 2002.

Reduced expression and promoter methylation of p16 gene in Epstein-Barr virusassociated gastric carcinoma. T Osawa, J M Chong, M Sudo, Japanese Journal of Cancer Research. 9311T. Osawa, J. M. Chong, M. Sudo et al., "Reduced expression and promoter methylation of p16 gene in Epstein-Barr virus- associated gastric carcinoma," Japanese Journal of Cancer Research, vol. 93, no. 11, pp. 1195-1200, 2002.

Aberrant methylation of multiple genes in gastric carcinomas. Y F Zhao, Y G Zhang, X X Tian, J Du, J Zheng, International Journal of Surgical Pathology. 153Y. F. Zhao, Y. G. Zhang, X. X. Tian, J. Du, and J. Zheng, "Aberrant methylation of multiple genes in gastric carcino- mas," International Journal of Surgical Pathology, vol. 15, no. 3, pp. 242-251, 2007.

Analysis of cell cycle regulators: p161NK4A, pRb, and CDK4 in low-and highgrade meningiomas. J Y M Tse, H K Ng, K W Lo, Human Pathology. 2911J. Y. M. Tse, H. K. Ng, K. W. Lo et al., "Analysis of cell cycle regulators: p161NK4A, pRb, and CDK4 in low-and high- grade meningiomas," Human Pathology, vol. 29, no. 11, pp. 1200-1207, 1998.

DNA methylation analysis techniques. C Dahl, P Guldberg, Biogerontology. 44C. Dahl and P. Guldberg, "DNA methylation analysis tech- niques," Biogerontology, vol. 4, no. 4, pp. 233-250, 2003.

Expression of retinoblastoma protein and P16 proteins in classic Hodgkin lymphoma: relationship with expression of p53 and presence of Epstein-Barr virus in the regulation of cell growth and death. L H Kim, S C Peh, S Poppema, Human Pathology. 371L. H. Kim, S. C. Peh, and S. Poppema, "Expression of retinoblastoma protein and P16 proteins in classic Hodgkin lymphoma: relationship with expression of p53 and presence of Epstein-Barr virus in the regulation of cell growth and death," Human Pathology, vol. 37, no. 1, pp. 92-100, 2006.

Elevated serum levels of transforming growth factor beta1 in Epstein-Barr virus-associated nasopharyngeal carcinoma patients. J Xu, J Menezes, U Prasad, A Ahmad, International Journal of Cancer. 84844J. Xu, J. Menezes, U. Prasad, and A. Ahmad, "Elevated serum levels of transforming growth factor beta1 in Epstein- Barr virus-associated nasopharyngeal carcinoma patients," International Journal of Cancer, vol. 8484, no. 4, pp. 396-399, 1999.

TGFbeta1, TGFbeta2, and TGFbeta3 protein expression in gastric carcinomas: correlation with prognostics factors and patient survival. K Vagenas, C Spyropoulos, V Gavala, A C Tsamandas, Journal of Surgical Research. 1392K. Vagenas, C. Spyropoulos, V. Gavala, and A. C. Tsamandas, "TGFbeta1, TGFbeta2, and TGFbeta3 protein expression in gastric carcinomas: correlation with prognostics factors and patient survival," Journal of Surgical Research, vol. 139, no. 2, pp. 182-188, 2007.

The expression of transforming growth factor-beta1 is significantly correlated with the expression of vascular endothelial growth factor and poor prognosis of patients with advanced gastric carcinoma. H Saito, S Tsujitani, S Oka, Cancer. 868H. Saito, S. Tsujitani, S. Oka et al., "The expression of transforming growth factor-beta1 is significantly correlated with the expression of vascular endothelial growth factor and poor prognosis of patients with advanced gastric carcinoma," Cancer, vol. 86, no. 8, pp. 1455-1462, 1999.

Role of transforming growth factor-β1 in invasion and metastasis in gastric carcinoma. Y Maehara, Y Kakeji, A Kabashima, Journal of Clinical Oncology. 172Y. Maehara, Y. Kakeji, A. Kabashima et al., "Role of trans- forming growth factor-β1 in invasion and metastasis in gastric carcinoma," Journal of Clinical Oncology, vol. 17, no. 2, pp. 607-614, 1999.

Does the expression of cyclin E, pRb, and p21 correlate with prognosis in gastric adenocarcinoma?. G Kouraklis, I E Katsoulis, S Theocharis, Digestive Diseases and Sciences. 545G. Kouraklis, I. E. Katsoulis, S. Theocharis et al., "Does the expression of cyclin E, pRb, and p21 correlate with prognosis in gastric adenocarcinoma?" Digestive Diseases and Sciences, vol. 54, no. 5, pp. 1015-1020, 2009.

Prognostic significance of immunohistochemical expression of p53 and retinoblastoma gene protein (pRB) in curatively resected gastric cancer. H S Song, I H Kim, S S Sohn, K Y Kwon, W S Lee, Korean Journal of Internal Medicine. 201H. S. Song, I. H. Kim, S. S. Sohn, K. Y. Kwon, and W. S. Lee, "Prognostic significance of immunohistochemical expression of p53 and retinoblastoma gene protein (pRB) in curatively resected gastric cancer," Korean Journal of Internal Medicine, vol. 20, no. 1, pp. 1-7, 2005.

Abnormal expression of pRb, p16, and Cyclin D1 in Gastric adenocarcinoma and its lymph node metastases: relationship with pathological features and survival. R M Feakins, C D Nickols, H Bidd, S J Walton, Human Pathology. 3412R. M. Feakins, C. D. Nickols, H. Bidd, and S. J. Walton, "Abnormal expression of pRb, p16, and Cyclin D1 in Gastric adenocarcinoma and its lymph node metastases: relationship with pathological features and survival," Human Pathology, vol. 34, no. 12, pp. 1276-1282, 2003.

Expression of altered retinoblastoma protein inversely correlates with tumor invasion in gastric carcinoma. N H Chou, H C Chen, N S Chou, P I Hsu, H H Tseng, World Journal of Gastroenterology. 1244N. H. Chou, H. C. Chen, N. S. Chou, P. I. Hsu, and H. H. Tseng, "Expression of altered retinoblastoma protein inversely correlates with tumor invasion in gastric carcinoma," World Journal of Gastroenterology, vol. 12, no. 44, pp. 7188-7191, 2006.

Abnormal expression of p16INK4a, cyclin D1, cyclin-dependent kinase 4 and retinoblastoma protein in gastric carcinomas. I Kishimoto, H Mitomi, Y Ohkura, H Kanazawa, N Fukui, M Watanabe, Journal of Surgical Oncology. 981I. Kishimoto, H. Mitomi, Y. Ohkura, H. Kanazawa, N. Fukui, and M. Watanabe, "Abnormal expression of p16INK4a, cyclin D1, cyclin-dependent kinase 4 and retinoblastoma protein in gastric carcinomas," Journal of Surgical Oncology, vol. 98, no. 1, pp. 60-66, 2008.

Expression of p16 gene and Rb protein in gastric carcinoma and their chinicopathological significance. X S He, Y H Rong, Q Su, World Journal of Gastroenterology. 1115X. S. He, Y. H. Rong, Q. Su et al., "Expression of p16 gene and Rb protein in gastric carcinoma and their chinicopathological significance," World Journal of Gastroenterology, vol. 11, no. 15, pp. 2218-2223, 2005.

Immunohistochemical expression of TGF-β1, p21WAF1, p53, Ki67, and angiogenesis in gastric carcinomas: a clinicopathologic study. V Zolota, A Batistatou, A C Tsamandas, G Iliopoulos, C D Scopa, D S Bonikos, International Journal of Gastrointestinal Cancer. 322-3V. Zolota, A. Batistatou, A. C. Tsamandas, G. Iliopoulos, C. D. Scopa, and D. S. Bonikos, "Immunohistochemical expression of TGF-β1, p21WAF1, p53, Ki67, and angiogenesis in gastric carcinomas: a clinicopathologic study," International Journal of Gastrointestinal Cancer, vol. 32, no. 2-3, pp. 83-89, 2002.


International Journal of Behavioral Nutrition and Physical Activity Reciprocal effects among changes in weight, body image, and other psychological factors during behavioral obesity treatment: a mediation analysis

António L Palmeira
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

University Lusófona de Humanidades e Tecnologias
Campo Grande1749-028LisbonPortugal

David A Markland
School of Sport, Health & Exercise Sciences
Bangor University
Holyhead RoadGeorge Building, BangorGwyneddUK

Marlene N Silva firstname.lastname@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Teresa L Branco firstname.lastname@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Sandra C Martins email@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Cláudia S Minderico cláudiasmindericofirstname.lastname@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Paulo N Vieira email@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

José T Barata
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Sidónio O Serpa sidóniooserpaemail@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Luis B Sardinha
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

Pedro J Teixeira email@example.com
Faculty of Human Kinetics
Technical University of Lisbon
Estrada da Costa, Cruz Quebrada1495-688Portugal

International Journal of Behavioral Nutrition and Physical Activity Reciprocal effects among changes in weight, body image, and other psychological factors during behavioral obesity treatment: a mediation analysis
10.1186/1479-5868-6-9BioMed Central Page 1 of 12 (page number not for citation purposes) Research * Corresponding author
Background: Changes in body image and subjective well-being variables (e.g. self-esteem) are often reported as outcomes of obesity treatment. However, they may, in turn, also influence behavioral adherence and success in weight loss. The present study examined associations among obesity treatment-related variables, i.e., change in weight, quality of life, body image, and subjective well-being, exploring their role as both mediators and outcomes, during a behavioral obesity treatment.Methods: Participants (BMI = 31.1 ± 4.1 kg/m 2 ; age = 38.4 ± 6.7 y) were 144 women who attended a 12-month obesity treatment program and a comparison group (n = 49), who received a general health education program. The intervention included regular group meetings promoting lasting behavior changes in physical activity and dietary intake. Body image, quality of life, subjective wellbeing, and body weight were measured at baseline and treatment's end. Mediation was tested by multiple regression and a resampling approach to measure indirect effects. Treatment group assignment was the independent variable while changes in weight and in psychosocial variables were analyzed alternatively as mediators and as dependent variables.Results: At 12 months, the intervention group had greater weight loss (-5.6 ± 6.8% vs. -1.2 ± 4.6%, p < .001) and larger decreases in body size dissatisfaction (effect size of 1.08 vs. .41, p < .001) than the comparison group. Significant improvements were observed in both groups for all other psychosocial variables (effect sizes ranging from .31-.75, p < .05). Mediation analysis showed that changes in body image and body weight were concurrently mediators and outcomes of treatment, suggesting reciprocal influences. Weight loss partially mediated the effect of treatment on quality of life and on self-esteem but the reciprocal effect was not observed.

Conclusion:

Changes in weight and body image may reciprocally affect each other during the course of behavioral obesity treatment. No evidence of reciprocal relationships was found for the other models under analysis; however, weight changes partially explained the effects of treatment on quality of life and self-esteem. Weight and psychosocial changes co-occur during treatment and will probably influence each other dynamically, in ways not yet adequately understood. Results from this study support the inclusion of intervention contents aimed at improving body image in weight management programs.

Background

Improving the treatment of overweight and obesity remains a critical challenge [1]. Several health behavior change models, often based on a social-cognitive framework, have been used to design weight management interventions, helping researchers improve treatment contents and conditions aiming at weight loss and maintenance [2]. However, most interventions have only produced modest weight reductions, especially in the long-term [3,4], and social-cognitive variables have shown limited power to predict weight outcomes [5,6]. Other predictors, and possibly alternative explanatory models, are needed to better understand the mechanisms by which successful weight management and other obesity treatment outcomes are more likely to occur [7][8][9][10].

Although findings are not entirely consistent, obesity intervention studies report improvements in other outcomes besides weight loss, such as body image, quality of life, self-esteem, and depression [11,12]. Results generally show that psychosocial outcomes are more evident in the long-term, and that they are not always associated with weight loss. For example, improved body image is inconsistently associated with treatment-related weight changes [13,14], whereas quality of life improvements -especially using obesity-specific measures -are more strongly associated with weight change [15]. One recent meta-analysis on the role of subjective well-being in obesity treatment suggested that self-esteem increases are dependent on weight loss, regardless of treatment group, whereas reductions in depression are independent of weight loss, but strongly associated with treatment [11]. Another metaanalysis showed that neither depression nor self-esteem improvements were associated with treatment condition; however, this study did not report associations between these variables and weight change [12]. These reports analyzed psychosocial changes primarily as outcomes of treatment. However, several authors have recommended that psychosocial changes should also be analyzed as mechanisms that can potentially contribute to better weight results, for example by mediating intervention effects on behavioral adherence and weight loss [16,17].

More than a decade ago, Friedman and Brownell recommended a "third generation" of obesity treatment studies, analyzing causal mechanisms and interactions between psychosocial variables and weight change [18]. Underlying their recommendation was the hypothesis that these paths might be intertwined and reflect reciprocal influences, which is coherent with the concept of reciprocal determinism between individual, environment, and behavior, central to Bandura's Social Cognitive Theory [19]. For example, a treatment might be effective partially because it increases psychological well-being, which in turn helps produce weight loss while, concurrently, weight changes might have also helped produce improved psychological well-being (e.g., body image or selfesteem). This phenomenon could be studied by reciprocal effects analysis, which is an extension of the traditional mediating model approach [2] and echoes the reciprocal effects model (REM) suggested by Marsh and colleagues in educational psychology research [20].

To our knowledge, reciprocal effects analyses have never been explored for weight loss and weight-related behaviors. Therefore, in the context of a 1-year behavior weight management program with adult women, the present study was designed to: a) analyze associations among treatment-related outcomes -changes in weight, quality of life, body image, and subjective well-being (i.e., selfesteem and depressive symptoms); and b) analyze the potential role of each of these variables as both mediators and outcomes, i.e., study reciprocal effects among these variables during (and as a result of) the treatment.

We predicted that intervention-related changes in body image and subjective well-being would both mediate and be mediated by weight change (i.e., reciprocal effects will be present), whereas quality of life would be mediated by weight change but not the reverse. Body image and subjective well-being variables have sometimes been associated with weight loss and their improvement during treatment is a consistent finding [13,14,17]. Therefore, they may be playing a double role as both mediators and outcomes, i.e., influencing and being influenced by weight loss. Conversely, obesity-specific measures of quality of life are consistently associated with both treatment participation and weight loss [11,12]. However, since these measures lead participants to reflect on quality of life as a consequence of their weight (e.g., 'because of my weight I am less pro-ductive than I could be'), we expect a one-way mediation to be present, from weight loss to improved quality of life (but not in the opposite direction).

Methods

Participants

Female participants were recruited from the community for two successive long-term weight management programs, which had very similar contents and intervention approaches, through newspaper ads, a website, email messages, and announcement flyers. Participants were required to be older than 24 years, pre-menopausal, not pregnant, have a BMI between 25 and 40 kg/m 2 , and be free from major disease, to be eligible for the studies. For the present analyses, we used only participants who had completed 12-month assessments, comprising 193 women in total (BMI = 31.1 ± 4.1 kg/m 2 ; Age = 38.4 ± 6.7 y). No differences were observed between 32 non-completers (14.3% attrition) and the 193 completers in the baseline assessments of the variables (p > .10). The intervention group (pooled from both studies, described below) included 144 participants. The comparison group had 49 participants, who did not receive a weight loss program. These participants derived from only one of the two studies, because in one of the designs all participants engaged in weight loss programs (with different levels of intervention). They received a general health education program comprising of 15 sessions covering topics such as stress management, general healthy eating, and cardiovascular risk reduction, among others. The intervention group was slightly older than the comparison group (39.0 ± 6.6 vs 36.6 ± 6.8 y, p = .032) and displayed lower selfesteem scores at baseline (p = .001), but there were no differences between groups with regard to weight, BMI, the proportion of participants who were obese (see Table 1), or other psychosocial variable. All participants agreed to refrain from participating in any other weight loss program and signed a written informed consent prior to participation in the study. The Faculty of Human Kinetic's Human Subjects Institutional Review Board approved the study.

Intervention

The intervention group sessions, which lasted for about 1 year, included exercise, nutrition, and behavior modification topics and were loosely based on the LEARN weight management program [21]. In one of the programs women (n = 81) met weekly with the intervention team for 4 months, then monthly for the remaining period. In the other, participants (n = 63) met weekly or every two weeks throughout the 12 months. Participants met with the intervention team in groups of approximately 30, for 120-150 min per session. The interventions included educational content and practical applications in the areas of physical activity and exercise, diet and eating behavior, behavior modification, and have been partially described before [5,22]. Physical activity topics included learning the energy cost associated with typical activities, increasing daily walking and lifestyle physical activity, planning and implementing a structured exercise plan, and choosing the right type of exercise, among many others. Examples of covered nutrition topics were learning the caloric, fat, and fiber content and the energy density of common foods, the role of breakfast and meal frequency for weight control, reducing portion size, and preventing binge and emotional eating. Cognitive and behavioral skills including self-monitoring, self-efficacy enhancement, dealing with lapses and relapses, enhancing body image, using contingency management strategies, and eliciting social support were also part of the curriculum. Sessions were conducted by the same team composed of Doctoral and Masters level exercise physiologists, psychologists, and dieticians. For each group, a group leader was selected from the intervention team to be present in all meetings. Participants were informed that weight reduction should be understood as a long-term goal, and that a 5-10% weight loss was an appropriate goal to be sought at the end of the program.

Instruments

Psychosocial Variables

Data were collected in two periods: a) baseline, corresponding to the pre-treatment scores; and b) at 12 months, which corresponded to the end of the treatment. The instruments were Portuguese validated versions of some of the most widely used psychosocial instruments in obesity research.

Body Image

Body Image was evaluated by two questionnaires commonly used to measure this construct, which were analyzed separately to consider body image's multidimensional nature [23]. Body size dissatisfaction (BSD) was measured with the Body Image Assessment questionnaire -BIA [24,25], which consists of nine silhouettes of increasing size, from which participants are asked to select the figures corresponding to their current (i.e., perceived actual body size) and their ideal body size. Body size dissatisfaction was calculated by subtracting the score for perceived body size from the ideal body size rating. Lower values indicate higher levels of body size dissatisfaction. The Body Shape Questionnaire -BSQ [25,26], a 34-item instrument scored on a 6-point Likert scale, was used to measure affective, cognitive, and behavioral dimensions of body image, especially regarding the experience of, and preoccupation with "being fat". The total score was used (α = .95), where higher values represent greater preoccupation with body shape (range .

Quality of Life

Obesity-specific quality of life was assessed using the Impact of Weight on Quality of Life -Lite -IWQOL-L [27,28], a 31-item questionnaire scored on a 5-point Likert scale. This measure results in five subscales and a total score in which higher values represent greater quality of life (range 0-100). Only the total score was used in the present study (α = .97).

Subjective Well-Being Self-esteem was assessed with the Rosenberg Self-Esteem Scale -RSES [29,30], composed of 10 items answered on a 4-point Likert scale. Higher scores on the RSES represent greater self-esteem (α = .76, range 10-40). Depressive symptoms were evaluated with the Beck Depression Inventory -BDI [31,32], a 21-item inventory measuring several symptoms of depression. It is scored on a 4-point scale and results in a total depression score (α = .91), where higher scores represent greater levels of depressive symptoms (range 0-63).

Body Weight

Body weight was lab-measured first thing in the morning in fasting conditions, with participants in light clothing, with a standardized procedure (average of three measures was used) at both baseline and treatment's end (12 months), using an electronic scale (SECA model 770, Hamburg, Germany).

Statistical Procedures

A mixed models ANOVA (time × group) was used to analyze the impact of the program on weight and psychosocial variables. Pearson correlation was used to examine associations between changes in weight and the psychosocial constructs. For correlational analysis, variables were expressed by the residuals of the 12-month value regressed on the baseline score. Using such residualized change scores is recommended as it creates a value that is orthogonal to the pre-treatment value(s) and represents a preferable measure of change, when compared with the pre-post subtraction procedure [33]. For ease of interpretation of the correlational results, body image and depres-sion scores were reversed, so that for all variables in the study higher scores always represent a more positive outcome.

To test the mediation models we used the procedures described by Preacher and Hayes [34], which use multiple linear regression analysis. Treatment vs. comparison was the independent variable, while changes in body weight, body image, quality of life, and subjective well-being played were tested both as mediators and dependent variables, consistent with the reciprocal effects model under analysis. Therefore, we had five reciprocal effect models, for a total of 10 regressions. For example, the two regression models for quality of life had the following structure: a) Independent variable: treatment group; Dependent variable: weight changes; Mediator: quality of life changes; and b) Independent variable: treatment group; Dependent variable: quality of life changes; Mediator: weight changes.

Reciprocal effects were considered to be present when significant mediation occurred in both regression models for a given construct. In the previous example, this would occur if both quality of life mediated treatment effects on weight and if weight changes mediated treatment effects on quality of life. This inference was made either with complete or partial mediation by the proposed mediators.

Preacher and Hayes [34] have recently provided a SPSS macro for the analyses of the causal steps criteria for mediation forwarded by Baron and Kenny [35] including Sobel tests, and also bootstrapped resampling results, for the specific indirect (or mediated) effects. We will present the resampling procedure (5000 bootstrap samples), via the Bias Corrected and Accelerated (BCa) estimates and 95% confidence intervals to present the indirect effects' significance. The BCa confidence intervals are considered by Preacher and Hayes [34] superior to the normal theory Sobel tests as they require no distributional assumptions and are less likely to lead to a Type I error. If the BCa 95% confidence interval does not include zero we can conclude there was a significant indirect effect (at alpha = .05). Collinearity was tested, resulting in variance inflation factors (1.10 -1.87) and tolerances (.53 -.91) within the limits accepted for regression analysis [33]. Homoscedasticity and linearity were observed through the analysis of residual scatterplots, revealing no problems.

Results

The analysis of the impact of the program on the design groups is presented in Table 2.

Weight loss was smaller in the comparison group (-1.2 ± 4.6%, p = .060) when compared to the intervention group (-5.6 ± 6.8%, p < .001). Body size dissatisfaction was reduced more effectively in the intervention group. All other variables improved during the program in both groups (p < .05), although treatment-related differences between groups were non-significant (see Table 2). Table 3 shows the intercorrelations among weight and psychosocial changes. Weight change was associated with changes in all psychosocial variables except depression. Among psychosocial variables, only self-esteem and body size dissatisfaction were not positively correlated.

The results of the reciprocal mediation analysis are presented next. Figure 1 contains a detailed description of each relationship in these models (useful to interpret Fig-ures 2 to 5). The top model (Xa) shows the mediation analysis for the prediction of weight change using mediator A as the mediator. The lower model (Xb) represents the reciprocal mediation analysis, i.e., the prediction of the dependent variable B (reciprocal mediator A), using weight change (reciprocally dependent variable A) as mediator. We have not included socio-demographic variables as covariates because in preliminary analyses they were not related to weight or psychosocial outcomes.

For example, in the first analysis for the reciprocal hypothesis in body size dissatisfaction (figure 2), the top model (1a) shows the mediation analysis for the prediction of weight change using body size dissatisfaction change as  mediator. The lower model (1b) represents the reciprocal mediation analysis, i.e., the prediction of body size dissatisfaction changes using weight change as mediator. The same approach will be used for the presentation of the remaining reciprocal mediation models.

The body size dissatisfaction mediation model (Figure 2, 1a), explained 26% of the weight change variance (F(2,164) = 29.43, p < .001). Total (p < .001), direct (p < .05), and indirect (95% BCa CI of 0.09 to 0.29) effects were significant. The weight change mediation model (Figure 2, 1b), explained 28% of body size dissatisfaction outcomes (F(2,164) = 32.21, p < .001). As in model 1a, all effects were significant, with total (p < .001), direct (p < .01) and indirect effects (95% BCa CI of 0.07 to 0.24) significantly influencing body size dissatisfaction changes. Results are consistent with the presence of a reciprocal effect between changes in weight and changes in body size dissatisfaction during (and as a result of) the intervention. As treatment reduced body size dissatisfaction, which in turn affected weight, weight loss also concurrently helped increase body satisfaction (see also Table 4 for a summary). Both models suggest the presence of partial mediation, since the direct effect, although reduced as evidenced by the significant indirect effects, remained significant when controlling for the mediator. Therefore, decreases in body size dissatisfaction during the program appeared to be one mechanism by which treatment affected body weight, while treatment-related weight changes affected body size dissatisfaction, albeit to a slightly lesser extent.

The body shape concerns mediation model (Figure 3, 2a) explained 23% of weight change (F(2,169) = 25.75, p < .001). The total (p < .001), direct (p < .01) and indirect effects (95% BCa CI of 0.01 to 0.14) were significant, therefore changes in body shape concerns partially mediated total treatment effects. The weight change mediation model (Figure 3, 2b) explained 17% of the variance in body shape concerns (F(3,169) = 16.83, p < .001). The indirect effects of weight change exerted a complete mediation of the effects of treatment on body shape (95% BCa CI of 0.08 to 0.23), since the significant total effect was reduced to a non-significant direct effect when controlling for the mediator. Results suggest reciprocal effects between changes in weight and body shape concerns during, and as a result of treatment. In other words, treatment reduced body shape concerns leading to weight loss, while reductions in weight were also associated with reductions in body shape concerns (see also Table 4). Weight loss appears to be a strong mechanism by which the intervention reduced concerns with body shape and feelings of being too fat. Mediation analysis for reciprocal change effects between weight and body shape concerns Mediation analysis for reciprocal change effects between weight and self-esteem The self-esteem mediation model ( Figure 5, 4a) explained 13% the variance in weight change (F(2,183) = 13.79, p < .001). Treatment total and direct effects were significant and the indirect effects were non-significant. Conversely, the weight change mediation model ( Figure 5, 4b) explained 5% of the variance in change in self-esteem (F(2,183) = 4.39, p = .014). Treatment effects were nonsignificant, whereas indirect effects were significant (95% BCa CI of 0.03 to 0.15). Results indicate the absence of reciprocal influences between changes in self-esteem and changes in weight during treatment (see also Table 4). These results are very similar to the weight-related quality of life model; only when treatment produced weight loss did the intervention improve self-esteem, since neither total nor direct effects were significant. Therefore, weight change had an indirect effect on the treatment related changes in self-esteem. Nevertheless, the total variance in the dependent variable explained by this model was very small (5%).

Indications to read the results of the reciprocal mediation-result figures

The depression mediation model explained 8% of weight change (F(2,125) = 5.45, p = .005). Total treatment effects were significant, whereas the indirect effect was non-significant. The weight change mediation model did not significantly predict depression (F(2,125) = 1.60, p = .206). These models were less predictive as a whole and do not support the reciprocal hypothesis (results not shown).

Discussion

This study examined the associations among obesity treatment-related variables -i.e., change in weight, quality of life, body image, and subjective well-being -, exploring their potential role as both mediators and outcomes and using a novel analysis approach. We found evidence to suggest that changes in weight and body image may reciprocally affect each other during obesity treatment. A reduction in body size dissatisfaction mediated the treatment effect on weight. The opposite effect (weight loss mediating less body dissatisfaction), although weaker, was also significant suggesting a reciprocal effect between the two variables. Conversely, change in body shape concerns was more dependent on weight outcomes. For the other psychosocial variables, despite no evidence of reciprocal relationships, we observed that weight change partially mediated the effect of treatment on both quality of life and self-esteem, in the expected direction (i.e., more weight loss as a result of treatment resulting in improved psychological outcomes).

The results for body size dissatisfaction suggest that this might have been one of several mechanisms by which the behavioral treatment influenced weight change. This measure of body dissatisfaction assesses self-ideal discrepancy, which can be affected by i) actual change in current body size (or the perception of it); ii) change in ideal body size, for instance, increasing acceptance of a larger than ideal shape/size; or iii) both [24]. The current results seem to point to the last hypothesis, considering the reciprocal effects observed between body size dissatisfaction and weight changes. Taking into account the positive social evaluation of a thin(ner) body, a norm which is internalized by so many people, especially women [16], it is easy to accept that weight loss would mediate improvements in body image during treatment. But could improvements in body image also (i.e. reciprocally) contribute to weight loss, as the present analysis suggests? In other words, might a decreased self-ideal discrepancy about one's body be causally related to improved adherence to the behaviors that lead to weight reduction?

This possibility has been suggested before by Baker and Brownell [36], who proposed that improvements in body image can lead to more adaptive eating and exercise behaviors. Also, Heinberg et al. [37] indicated that there may be an inverted U-shaped relationship between body image dissatisfaction and motivation to lose weight, suggesting that participants who maintain large discrepancies between their perceived actual and ideal body shapes may be caught in a cycle of negative psychological processes (e.g., negative self-talk, rumination, hopelessness) that are debilitating and inhibit change. Furthermore, the lack of progress towards their idealized body size should undermine expectations, possibly resulting in motivational impairments and maladjusted eating behavior patterns [38,39]. Recently, two studies reported mechanisms that might explain these processes regarding physical activity adherence [40,41]. In one of these studies, results showed that higher body size discrepancies were significantly associated with less relative autonomy for exercise in female adolescents [41]. The authors suggested that negative body image leads to less autonomous motivations to exercise, perhaps by increasing the felt pressure to conform to social norms, which in turn inhibits exercise engagement. In the other study [40], with adult females, body size discrepancies exerted a negative influence on physical activity through decreases in the feelings that exercise is a valued and enjoyable activity. We suggest that the body image improvement contents of the treatment, which focused on the development of internal instead of externally or social driven values, could also have helped reduce perceived social pressures and directed the participants towards self-investment and self-acceptance, promoting the development of more autonomous motivations towards behavior change [42].

The second model that dealt with body image showed that weight loss completely mediated treatment effects on body shape concerns, showing that this facet of body image was more dependent on actual weight changes than body size dissatisfaction. Body shape concerns represent distressing preoccupations about weight and shape, embarrassment in public, avoidance of activity (or exposure of the body) due to self-consciousness, and excessive feelings of fatness after eating [26]. Several items in the Body Shape Questionnaire target aspects which seem directly dependent on actual body size and fatness ("When in company have you worried about taking up too much room, e.g., sitting on a sofa or a bus seat?", "Have you avoided running because your flesh might wobble?"). As such, treatment-related increases in body acceptance or changes in what constitutes an ideal body size might not impact this measure of body image as much as they influenced body size dissatisfaction.

In the quality of life models, we observed that only when treatment produced weight loss did the intervention result in improved weight-related quality of life. These results extend previous findings [12,43], where the impact of weight on quality of life was associated with both treatment participation and weight loss. Furthermore, the IWQOL-lite questionnaire is a weight-specific instrument, all of its items starting with the sentence "Because of my weight...". As a result, it is expected that weight change would mediate outcomes in this variable. Several previous studies have shown the IWQOL-lite scores to be strongly correlated with both BMI or body weight change [27,28]. It was interesting to note that despite no significant direct effects of treatment on quality of life, the treatment influence on weight (i.e., the interactive effects of treatment group and weight changes) appeared to predict changes in quality of life (see Figure 4). This situation was addressed by Kraemer et al. [44], who argued that the definition of a mediator does not necessarily imply the existence of treatment main effects, but that an interactive effect is sufficient. In the present study, treatment appears to have significantly influenced not only the level of the mediator (i.e., weight change) but also its nature, by "specifying" or creating the conditions under which it influenced a specific outcome (quality of life), even in the absence of differences between intervention and comparison groups for change in this variable.

According to Fox's physical self-perception model [45], global self-esteem stands hierarchically higher than bodyesteem constructs. Therefore, we expected that the associations between changes in body image and weight might be paralleled in the results for self-esteem. However, only weight change affected self-esteem, without support for the reciprocal hypothesis (weight change being mediated by self-esteem change). This result replicates findings recently presented in a meta-analysis of well-being outcomes in weight loss treatments [11]. In that review, Blaine and colleagues proposed that weight loss influences self-esteem responses to treatment because significant reductions in weight prompt participants to internalize the more positive body-related appraisals they imagine others to have of them. In the present study, selfesteem was significantly associated with body shape concerns and with quality of life (but not with body size dissatisfaction), variables showing the same pattern of association with weight.

We observed that depressive symptoms improved in both intervention and comparison groups and were not a mechanism that influenced weight loss, nor were improvements in depression mediated by weight changes. These findings partially support previous reports where depression was associated with treatment (not the case in the present study), but not to weight loss. It is worth mentioning that the comparison group in our analysis did participate in a health education program. It involved less intervention contact and did not focus on weight but it might, nevertheless, have influenced participants' wellbeing, namely by social interaction with their group, by the continued contact with health professionals, and by some of the topics covered within the health education program (e.g., stress and time management).

Conclusion

The primary concept under scrutiny in the current report was that treatment-related weight change and changes in selected psychological processes reciprocally affect each other during treatment. We tested this "reciprocal mediation" model for several variables usually considered as outcomes of weight loss programs, and found confirmation of our hypotheses for body image, especially body size dissatisfaction. Contrarily, the present results indicate that obesity-specific quality of life and self-esteem were affected by weight loss success but without reciprocal influences back on weight loss. To the extent psychosocial variables prove to be more than outcomes, as appears to be the case for body image, then the inclusion of contents to specifically change them during obesity treatment is clearly warranted [46]. We suggest that future studies follow this reciprocal mediation analysis procedure in randomized controlled trials with longer time periods, preferably with more than the two data points we have included in the present analysis, and include other variables such as motivation-related constructs (e.g., intrinsic motivation) or more classical social-cognitive variables (e.g, attitudes, perceived behavioral control). The inclusion of variables which are potentially moderating the effects of treatment (e.g number of previous diets, autonomous orientation [6]) might also be considered. The mediation and reciprocal effects analysis could be more elucidating in a study with these characteristics, thus providing more information about the dynamical mechanisms underlying weight management and help researchers improve the contents and conditions of obesity treatments.

Figure 1 (
1Indications to read the results of the reciprocal mediation-result figures. Note for Figure 1. All values are standardized coefficients (except for the R 2 ); IV -Independent Variable; DV -Dependent Variable. International Journal of Behavioral Nutrition and Physical Activity 2009, page number not for citation purposes) Mediation analysis for the reciprocal change effects between weight and body size dissatisfaction Figure 2 Mediation analysis for the reciprocal change effects between weight and body size dissatisfaction. Note for Figure 2. See note for figure 1 for more information. *p < .05; **p < .01; ***p < .001. ¥ -The 95% CI of the Bias and Corrected and Accelerated estimate indicate a significant indirect effect.

Figure 3 (
3Mediation analysis for reciprocal change effects between weight and body shape concerns. Note for Figure 3. See note for figure 1 for more information. *p < .05; **p < .01; ***p < .001. ¥ -The 95% CI of the Bias and Corrected and Accelerated estimate indicate a significant indirect effect. International Journal of Behavioral Nutrition and Physical Activity 2009, page number not for citation purposes) Mediation analysis for reciprocal change effects between weight and weight related quality of life Figure 4 Mediation analysis for reciprocal change effects between weight and weight related quality of life. Note for Figure 4. See note for figure 1 for more information. *p < .05; **p < .01; ***p < .001. ¥ -The 95% CI of the Bias and Corrected and Accelerated estimate indicate a significant indirect effect. QOL -Quality of Life.

Figure 5
5Mediation analysis for reciprocal change effects between weight and self-esteem. Note forFigure 5. See note for figure 1 for more information. *p < .05; **p < .01; ***p < .001. ¥ -The 95% CI of the Bias and Corrected and Accelerated estimate indicate a significant indirect effect.The weight-related quality of life mediation model (Figure 4, 3a) explained 27% of weight change (F(2,172) = 32.08, p < .001). Treatment total and direct effects were significant, while the indirect effect was non-significant (i.e., no mediation). The weight change mediation model (Figure 4, 3b) explained 20% of quality of life treatment-related outcomes (F(2,172) = 21.75, p < .001). Contrary to the previous model, treatment effects were non-significant, whereas the indirect effect was significant (95% BCa CI of 0.10 to 0.26). Results do not support the presence of reciprocal effects. Weight change had an indirect effect of treatment-related changes in quality of life (model 3b) consistent with treatment producing weight loss which in turn positively affects weight-related quality of life. This situation occurred despite no main effects being detected for treatment impact on quality of life (intervention vs comparison), as neither the total nor the direct effects were significant. Thus, only when treatment affected weight did the intervention produce better weight-related quality of life. However, the alternative model showed that changes in weight-related quality of life did not play a role in the treatment effect on weight change.

Table 1 :
1Baseline demographic and anthropometric characteristics of the participantsIntervention (n = 144)
Comparison (n = 49)
M ± SD
M ± SD

Weight (kg)
80.7 ± 12.2
79.7 ± 12.6
BMI (kg/m 2 )
31.2 ± 4.2
30.7 ± 3.8
Age (years)
39.0 ± 6.6
36.6 ± 6.8

Percentage
Percentage
% Obese
57.1
56.3

Note: No differences between groups, except for age (p = .032)

Table 2 :
2Means, standard deviations, effect sizes and mixed model ANOVA to analyze the impact of the program on the interventionNote: ES -effect size. QOL -Quality of Life.(n = 144) vs comparison (n = 49) groups

Baseline
12 Months
Time × Group

Variables
M ± SD
M ± SD
ES
F
p

Weight (kg)
Comparison
79.7 ± 12.6
78.7 ± 12.3
-0.09
16.79
<.001
Intervention
80.7 ± 12.2
76.1 ± 12.1
-0.38
Body Image
Body size dissatisfaction
Comparison
2.5 ± 0.8
2.2 ± 0.8
-0.41
12.11
<.001
Intervention
2.4 ± 0.7
1.6 ± 0.7
-1.08
Body shape concerns
Comparison
99.0 ± 22.1
85.2 ± 24.2
-0.60
2.45
0.120
Intervention
96.5 ± 27.7
76.1 ± 26.4
-0.75
Quality of Life
Weight-Related QOL
Comparison
73.8 ± 13.9
82.2 ± 12.2
0.64
0.22
0.639
Intervention
79.5 ± 13.5
87.0 ± 10.3
0.63
Subjective Well-Being
Self-esteem
Comparison
33.0 ± 4.1
34.3 ± 4.5
0.31
2.18
0.140
Intervention
30.5 ± 4.4
32.8 ± 4.4
0.52
Depression
Comparison
6.8 ± 4.6
3.8 ± 3.5
-0.75
0.50
0.480
Intervention
6.6 ± 4.7
4.4 ± 4.4
-0.49

Table 3 :
3Quality of Life. The Body Size Dissatisfaction does not have an internal consistency value.Internal consistency (Alpha) for psychosocial variables and intercorrelations among weight and psychosocial changes (n =
193).

Alpha
Weight Change
1
2
3
4

Body Image Changes
1 Body size dissatisfaction
-.49 ***
2 Body shape concerns
.95
-.41 ***
.33 ***
Quality of Life Changes
3 Weight-Related QOL
.97
-.45 ***
.37 ***
.60 ***
Subjective Well-Being Changes
4 Self-esteem
.76
-.21 **
.08
.37 ***
.41 ***
5 Depression
.91
-.14
.18 *
.33 ***
.36 ***
.20 *

Note: *p < .05, **p < .01; ***p < .001. QOL -

Table 4 :
4Summary of the mediation analysis and support for the reciprocal effects modelModel Meadiator
Outcome
Classification
Notes

Body Size Dissatisfaction

1a
Δ BSD
Δ Weight
Partially mediates Δ Weight
Partial support for REM. Slightly stronger effects of changes in body
dissatisfaction on weight changes than the opposite model.
1b
Δ Weight
Δ BSD
Partially mediates Δ BSD

Body Shape Concerns

2a
Δ BSQ
Δ Weight
Partially mediates Δ Weight
Partial support for REM. Weight loss mediation was stronger on body
shape concerns than the opposite model.
2b
Δ Weight
Δ BSQ
Fully mediates Δ BSQ

Weight-Related Quality of Life

3a
Δ WR-QoL
Δ Weight
Irrelevant to Δ Weight
No support for REM. Weight loss has an indirect effect on quality of life
improvements.
3b
Δ Weight
Δ WR-QoL
Indirect effect on Δ WR-QoL

Self-esteem Change

4a
Δ Self-esteem
Δ Weight
Irrelevant to Δ Weight
No support for REM. Weight loss has an indirect effect on self-esteem
improvements.
4b
Δ Weight
Δ Self-esteem Indirect effect on Δ Self-esteem

Depression Change

5a
Δ Depression
Δ Weight
Irrelevant to Δ Weight
No support for REM.
5b
Δ Weight
Δ Depression
Irrelevant to Δ Depression

Note: Δ -Difference from baseline to program's end; REM -Reciprocal effect model; BSD -Body Size Dissatisfaction; BSQ -Body Shape
Concerns; WR-QoL -Weight-Related Quality of Life.

(page number not for citation purposes)
AcknowledgementsThis study was funded by the Portuguese Science and Technology Foundation and by the Oeiras City Council. The investigators are grateful to Roche Pharmaceuticals Portugal, Becel Portugal, and Compal Portugal for small grants and donations. We also wish to thank all women who participated in the trial for their commitment to this research project.Competing interestsThe authors declare that they have no competing interests.Authors' contributionsALP and PJT conceived the study and drafted the manuscript. ALP performed the statistical analysis, was responsible for psychometric assessments and participated in the intervention's implementation. DAM participated in the study's conception and was the statistical advisor. MNS, PNV, TLB, SSM, CSM, and JTB actively participated in the intervention's implementation and in data collection. SOS participated in the study design and in the selection of psychosocial predictors. LBS is a principal investigator in the research trial. All authors read and approved the final manuscript.
Effective obesity treatments. L H Powell, J E Calvin, J E CalvinJr, Am Psychol. 62Powell LH, Calvin JE 3rd, Calvin JE Jr: Effective obesity treat- ments. Am Psychol 2007, 62:234-246.

Are current health behavioral change models helpful in guiding prevention of weight gain efforts?. T Baranowski, K W Cullen, T Nicklas, D Thompson, J Baranowski, Obes Res. 11SupplBaranowski T, Cullen KW, Nicklas T, Thompson D, Baranowski J: Are current health behavioral change models helpful in guid- ing prevention of weight gain efforts? Obes Res 2003, 11(Suppl):23S-43S.

Obesity: responding to the global epidemic. T A Wadden, K D Brownell, G D Foster, J Consult Clin Psychol. 70Wadden TA, Brownell KD, Foster GD: Obesity: responding to the global epidemic. J Consult Clin Psychol 2002, 70:510-525.

Successful weight loss maintenance. R R Wing, J O Hill, Annu Rev Nutr. 21Wing RR, Hill JO: Successful weight loss maintenance. Annu Rev Nutr 2001, 21:323-341.

Predicting short-term weight loss using four leading health behavior change theories. A L Palmeira, P J Teixeira, T L Branco, S S Martins, C S Minderico, J T Barata, S O Serpa, L B Sardinha, Int J Behav Nutr Phys Act. 414Palmeira AL, Teixeira PJ, Branco TL, Martins SS, Minderico CS, Barata JT, Serpa SO, Sardinha LB: Predicting short-term weight loss using four leading health behavior change theories. Int J Behav Nutr Phys Act 2007, 4:14.

A review of psychosocial pre-treatment predictors of weight control. P J Teixeira, S B Going, L B Sardinha, T G Lohman, Obes Rev. 6Teixeira PJ, Going SB, Sardinha LB, Lohman TG: A review of psy- chosocial pre-treatment predictors of weight control. Obes Rev 2005, 6:43-65.

A chaotic view of behavior change: a quantum leap for health promotion. K Resnicow, R Vaughan, Int J Behav Nutr Phys Act. 325Resnicow K, Vaughan R: A chaotic view of behavior change: a quantum leap for health promotion. Int J Behav Nutr Phys Act 2006, 3:25.

Crisis and chaos in behavioral nutrition and physical activity. T Baranowski, Int J Behav Nutr Phys Act. 327Baranowski T: Crisis and chaos in behavioral nutrition and physical activity. Int J Behav Nutr Phys Act 2006, 3:27.

Order is needed to promote linear or quantum changes in nutrition and physical activity behaviors: a reaction to 'A chaotic view of behavior change' by Resnicow and Vaughan. J Brug, Int J Behav Nutr Phys Act. 329Brug J: Order is needed to promote linear or quantum changes in nutrition and physical activity behaviors: a reac- tion to 'A chaotic view of behavior change' by Resnicow and Vaughan. Int J Behav Nutr Phys Act 2006, 3:29.

How can Health Behavior Theory be made more useful for intervention research?. R W Jeffery, Int J Behav Nutr Phys Act. 110Jeffery RW: How can Health Behavior Theory be made more useful for intervention research? Int J Behav Nutr Phys Act 2004, 1:10.

Weight loss treatment and psychological well-being: a review and meta-analysis. B E Blaine, J Rodman, J M Newman, J Health Psychol. 12Blaine BE, Rodman J, Newman JM: Weight loss treatment and psychological well-being: a review and meta-analysis. J Health Psychol 2007, 12:66-82.

A structured review of randomized controlled trials of weight loss showed little improvement in health-related quality of life. M L Maciejewski, D L Patrick, D F Williamson, J Clin Epidemiol. 58Maciejewski ML, Patrick DL, Williamson DF: A structured review of randomized controlled trials of weight loss showed little improvement in health-related quality of life. J Clin Epidemiol 2005, 58:568-578.

Body image in obese women before, during, and after weight loss treatment. G D Foster, T A Wadden, R A Vogt, Health Psychol. 16Foster GD, Wadden TA, Vogt RA: Body image in obese women before, during, and after weight loss treatment. Health Psychol 1997, 16:226-229.

A comparison of weight control and weight control plus body image therapy for obese men and women. E M Ramirez, J C Rosen, J Consult Clin Psychol. 69Ramirez EM, Rosen JC: A comparison of weight control and weight control plus body image therapy for obese men and women. J Consult Clin Psychol 2001, 69:440-446.

The relationship between health-related quality of life and weight loss. R L Kolotkin, R D Crosby, G R Williams, G G Hartley, S Nicol, Obes Res. 9Kolotkin RL, Crosby RD, Williams GR, Hartley GG, Nicol S: The relationship between health-related quality of life and weight loss. Obes Res 2001, 9:564-571.

Obesity and Body Image. M B Schwartz, K D Brownell, Body Image. 1Schwartz MB, Brownell KD: Obesity and Body Image. Body Image 2004, 1:43-56.

B G Berger, Subjective Well-Being in Obese Individuals: the Multiple Roles of Exercise. 56Berger BG: Subjective Well-Being in Obese Individuals: the Multiple Roles of Exercise. Quest 2004, 56:50-76.

Psychological correlates of obesity: moving to the next research generation. M A Friedman, K D Brownell, Psychol Bull. 117Friedman MA, Brownell KD: Psychological correlates of obesity: moving to the next research generation. Psychol Bull 1995, 117:3-20.

Self-Efficacy. The Exercise of Control New York: W.H. Freeman and Company. A Bandura, Bandura A: Self-Efficacy. The Exercise of Control New York: W.H. Free- man and Company; 1997.

Reciprocal Effects of Self-Concept and Performance From a Muldimensional Perspective. H W Marsh, R G Craven, Perspectives on Psychological Science. 1Marsh HW, Craven RG: Reciprocal Effects of Self-Concept and Performance From a Muldimensional Perspective. Perspec- tives on Psychological Science 2006, 1:133-163.

K D Brownell, The LEARN program for weight control. Dallas, TXAmerican Health Publishing CompanyBrownell KD: The LEARN program for weight control Dallas, TX: Amer- ican Health Publishing Company; 1997.

Who will lose weight? A cross-cultural reexamination of predictors of weight loss in women. P J Teixeira, A L Palmeira, T L Branco, S S Martins, C M Minderico, J T Barata, A M Silva, L B Sardinha, Int J Behav Nutr Phys Act. 112Teixeira PJ, Palmeira AL, Branco TL, Martins SS, Minderico CM, Bar- ata JT, Silva AM, Sardinha LB: Who will lose weight? A cross-cul- tural reexamination of predictors of weight loss in women. Int J Behav Nutr Phys Act 2004, 1:12.

Body image: past, presente, and future. T Cash, Body Image. 1Cash T: Body image: past, presente, and future. Body Image 2003, 1:1-5.

Development of a simple procedure for assessing body image disturbances. D A Williamson, C J Davis, S M Bennett, A J Goreczny, D H Gleaves, Behav Asses. 11Williamson DA, Davis CJ, Bennett SM, Goreczny AJ, Gleaves DH: Development of a simple procedure for assessing body image disturbances. Behav Asses 1989, 11:433-446.

Portuguese Validation of the Body Shape Concerns Questionnaire. P Vieira, A L Palmeira, C Francisco, P J Teixeira, Validação Portuguesa do Questionário de Forma CorporalVieira P, Palmeira AL, Francisco C, Teixeira PJ: Portuguese Valida- tion of the Body Shape Concerns Questionnaire [Validação Portuguesa do Questionário de Forma Corporal].

Lisbon Portuguese Society of Health Psychology. Lisbon Portuguese Society of Health Psy- chology; 2004.

The development and validation of a body shape questionnaire. P J Cooper, M J Taylor, Z Cooper, C G Fairburn, Int J Eating Disorders. 6Cooper PJ, Taylor MJ, Cooper Z, Fairburn CG: The development and validation of a body shape questionnaire. Int J Eating Disor- ders 1987, 6:485-494.

Psychometric and Cross-National Evaluation of a Portuguese Version of the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) Questionnaire. European Eating Disorders Review. S G Engel, R L Kolotkin, P J Teixeira, L B Sardinha, P N Vieira, A L Palmeira, R D Crosby, 13Engel SG, Kolotkin RL, Teixeira PJ, Sardinha LB, Vieira PN, Palmeira AL, Crosby RD: Psychometric and Cross-National Evaluation of a Portuguese Version of the Impact of Weight on Quality of Life-Lite (IWQOL-Lite) Questionnaire. European Eating Dis- orders Review 2005, 13:133-143.

Development of a brief measure to assess quality of life in obesity. R L Kolotkin, R D Crosby, K D Kosloski, G R Williams, Obes Res. 9Kolotkin RL, Crosby RD, Kosloski KD, Williams GR: Development of a brief measure to assess quality of life in obesity. Obes Res 2001, 9:102-111.

Society and the adolescent self-image. M Rosenberg, Princeton University PressPrinceton, NJRosenberg M: Society and the adolescent self-image Princeton, NJ: Prin- ceton University Press; 1965.

Self-esteem in the scholl secondary level: Validation of the Rosenberg Self-Esteem Scale [A autoestima no ensino secundário: Validação da Rosenberg Self-Esteem Scale. A Azevedo, L Faria, Azevedo A, Faria L: Self-esteem in the scholl secondary level: Validation of the Rosenberg Self-Esteem Scale [A auto- estima no ensino secundário: Validação da Rosenberg Self- Esteem Scale].

C Machado, L S Almeida, M Gonçalves, Braga, Avaliação Psicológica Formas e Contextos. Universidade do MinhoIn Avaliação Psicológica Formas e Contextos Edited by: Machado C, Almeida LS, Gonçalves M. Braga: Universidade do Minho; 2004:415-421.

A T Beck, R A Steer, Manual for the Beck Depression Inventory New York: Psychological Corporation. Beck AT, Steer RA: Manual for the Beck Depression Inventory New York: Psychological Corporation; 1987.

Manual for the Portuguese Version of Beck Scales. [Manual da versão em português das escalas de Beck] São Paulo: Casa do Psicólogo/ The Psychological Corporation. J A Cunha, Cunha JA: Manual for the Portuguese Version of Beck Scales. [Manual da versão em português das escalas de Beck] São Paulo: Casa do Psicólogo/ The Psychological Corporation; 2001.

Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. J Cohen, P Cohen, S G West, L S Aiken, Laurence Erlbaum AssociatesMahwah, New Jersey3rd editionCohen J, Cohen P, West SG, Aiken LS: Applied Multiple Regression/Cor- relation Analysis for the Behavioral Sciences 3rd edition. Mahwah, New Jersey: Laurence Erlbaum Associates; 2003.

Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. K J Preacher, A F Hayes, Behav Res Methods. 40Preacher KJ, Hayes AF: Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods 2008, 40:879-891.

The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. R M Baron, D A Kenny, Journal of Personality and Social Psychology. 51Baron RM, Kenny DA: The moderator-mediator variable dis- tinction in social psychological research: Conceptual, strate- gic, and statistical considerations. Journal of Personality and Social Psychology 1986, 51:1173-1182.

Physical Activity and Maintnence of Weight Loss: Physiological and Psychological Mechanisms. C W Baker, K D Brownell, In Physical Activity and Obesity Edited by: Bouchard C. Champaing, IL.: Human Kinetics. Baker CW, Brownell KD: Physical Activity and Maintnence of Weight Loss: Physiological and Psychological Mechanisms. In Physical Activity and Obesity Edited by: Bouchard C. Champaing, IL.: Human Kinetics; 2000:311-328.

Body Image Dissatisfaction as a Motivator for Healthy Lifestyle Change: Is Some Distress Beneficial?. L J Heinberg, J K Thompson, J L Matzon, Eating Disorders: Innovative directions in research and pratice Edited by: Striegel. Moore RH, Smolak L. WashingtonAmerican Psychological AssociationHeinberg LJ, Thompson JK, Matzon JL: Body Image Dissatisfaction as a Motivator for Healthy Lifestyle Change: Is Some Dis- tress Beneficial? In Eating Disorders: Innovative directions in research and pratice Edited by: Striegel-Moore RH, Smolak L. Washington: American Psychological Association; 2001.

Psychological and behavioral predictors of weight loss during drug treatment for obesity. L G Womble, D A Williamson, F L Greenway, S M Redmann, Int J Obes Relat Metab Disord. 25Womble LG, Williamson DA, Greenway FL, Redmann SM: Psycho- logical and behavioral predictors of weight loss during drug treatment for obesity. Int J Obes Relat Metab Disord 2001, 25:340-345.

Body image partially mediates the relationship between obesity and psychological distress. K E Friedman, S K Reichmann, P R Costanzo, G J Musante, Obes Res. 10Friedman KE, Reichmann SK, Costanzo PR, Musante GJ: Body image partially mediates the relationship between obesity and psy- chological distress. Obes Res 2002, 10:33-41.

D A Markland, The mediating role of behavioural regulations in the relationship between perceived body size discrepancies and physical activity among adult women. Hellenic Journal of. Psychology in pressMarkland DA: The mediating role of behavioural regulations in the relationship between perceived body size discrepancies and physical activity among adult women. Hellenic Journal of Psychology in press.

The relationships between body mass and body image and relative autonomy for exercisenext term among adolescent males and females. D A Markland, D K Ingledew, Psychology Sport and Exercise. 8Markland DA, Ingledew DK: The relationships between body mass and body image and relative autonomy for exercisen- ext term among adolescent males and females. Psychology Sport and Exercise 2007, 8:836-853.

Motivational predictors of weight loss and weight-loss maintenance. G C Williams, V M Grow, Z R Freedman, R M Ryan, E L Deci, J Pers Soc Psychol. 70Williams GC, Grow VM, Freedman ZR, Ryan RM, Deci EL: Motiva- tional predictors of weight loss and weight-loss maintenance. J Pers Soc Psychol 1996, 70:115-126.

Quality of life and obesity. R L Kolotkin, K Meter, G R Williams, Obes Rev. 2Kolotkin RL, Meter K, Williams GR: Quality of life and obesity. Obes Rev 2001, 2:219-229.

Mediators and moderators of treatment effects in randomized clinical trials. H C Kraemer, G T Wilson, C G Fairburn, W S Agras, Arch Gen Psychiatry. 59Kraemer HC, Wilson GT, Fairburn CG, Agras WS: Mediators and moderators of treatment effects in randomized clinical tri- als. Arch Gen Psychiatry 2002, 59:877-883.

The Physical Self-Perception Profile manual DeKalb, IL: Northern Illinois University. K R Fox, Fox KR: The Physical Self-Perception Profile manual DeKalb, IL: North- ern Illinois University; 1990.

Improving Body Image in Obesity. J C Rosen, Body Image, Eating Disorders, and Obesity: An Integrative Guide for Assessment and Treatment Edited by: Thompson JK. Washington, DCAPARosen JC: Improving Body Image in Obesity. In Body Image, Eat- ing Disorders, and Obesity: An Integrative Guide for Assessment and Treat- ment Edited by: Thompson JK. Washington, DC: APA; 2003:425-440.