Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis.

OBJECTIVE: To determine if specific dietary patterns are associated with breast cancer (BC) risk in Chinese women. DESIGN: Latent class analysis (LCA) was performed to identify generic dietary patterns based on daily food-frequency data. SETTING: The Chinese Wuxi Exposure and Breast Cancer Study (2013-2014). PARTICIPANTS: A population-based case-control study (695 cases, 804 controls). RESULTS: Four dietary patterns were identified, Prudent, Chinese traditional, Western and Picky; the proportion in the controls and cases was 0·30/0·32/0·16/0·23 and 0·29/0·26/0·11/0·33, respectively. Women in Picky class were characterised by higher extreme probabilities of non-consumption of specific foods, the highest probabilities of consumption of pickled foods and the lowest probabilities of consumption of cereals, soya foods and nuts. Compared with Prudent class, Picky class was associated with a higher risk (OR = 1·42, 95 % CI 1·06, 1·90), while the relevant association was only in post- (OR = 1·44, 95 % CI 1·01, 2·05) but not in premenopausal women. The Western class characterised by high-protein, high-fat and high-sugar foods, and the Chinese traditional class characterised by typical consumption of soya foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did. CONCLUSIONS: LCA captures the heterogeneity of individuals embedded in the population and could be a useful approach in the study of dietary pattern and disease. Our results indicated that the Picky class might have a positive association with the risk of BC.

Fresh vegetable and fruit consumption and carotid atherosclerosis in high-cardiovascular-risk population: a cross-sectional study in Jiangsu, China / Consumo de frutas e verduras frescas e aterosclerose carotídea em uma população de alto risco cardiovascular: um estudo transversal em Jiangsu, China / Consumo de verduras frescas y fruta y la aterosclerosis carotídea en una población con alto riesgo cardiovascular: un estudio trasversal en Jiangsu, China

This study aimed to investigate the association of vegetable and fruit consumption with carotid plaque (CP) and carotid intima-media thickness (CIMT), two predictors of carotid atherosclerosis, within urban and rural adults at high risk of developing cardiovascular diseases (CVDs) in regional China. A total of 11,392 adults at high CVD risk were identified from general population of 71,511 in this cross-sectional study, conducted between November of 2015 and May of 2016 in the Jiangsu Province. Among these 11,392 high risk participants, CP prevalence was 36.7%. The independent variables, vegetable and fruit intake frequency, were assessed by a food frequency questionnaire. The outcome variables, CIMT and CP, were measured by ultrasound examination. The ANCOVA analysis showed no association between CIMT values and vegetable and fruit intake frequencies. Multivariate logistic regression models were introduced to examine the association between vegetable and fruit intake and CP. After adjustment for potential confounders, the odds ratios (ORs) for participants who occasionally and daily consumed vegetable to experience any CP were 0.67 (95%CI: 0.58-0.78) and 0.70 (95%CI: 0.62-0.79), respectively, compared with those rarely consumed vegetable. While the adjusted ORs were 0.77 (95%CI: 0.64-0.92) and 0.80 (95%CI: 0.68-0.94), separately, for occasional and daily vegetable consumers to develop single CP relative to their counterparts who rarely consumed any vegetables. However, no significant association between fruit consumption and CP was observed. Among the Chinese population at high CVD risk, consumption of fresh vegetables was negatively associated with the risk of developing carotid plaque.

O estudo buscou investigar a associação entre consumo de frutas e verduras e placa carotídea (PC) e espessura íntima-média carotídea (EIMC), dois preditores de aterosclerose entre adultos das áreas urbana e rural com alto risco de desenvolver doenças cardiovasculares (DCVs) em uma região da China. Foram identificados 11.392 adultos com alto risco de DCV, entre 71.511 indivíduos da população geral, em um estudo transversal entre novembro de 2015 e maio de 2016 na Província de Jiangsu. Entre esses 11.392 participantes de alto risco, a prevalência de PC foi de 36,7%. As variáveis independentes, ou seja, frequências de consumo de frutas e verduras, foram avaliadas através de um questionário de frequência alimentar. As variáveis de desfecho, EIMC e PC, foram medidas por ultrassom. A análise ANCOVA não mostrou associação entre valores de EIMC e frequências de consumo de frutas e verduras. Foram introduzidos modelos de regressão logística multivariada para examinar a associação entre consumo de frutas e verduras e PC. Depois de ajustar para potenciais fatores de confusão, as ORs para participantes com consumo eventual e diário de verduras para qualquer PC foram 0,67 (IC95%: 0,58-0,78) e 0,70 (IC95%: 0,62-0,79), respectivamente, comparado com aqueles com consumo raro de verduras. Enquanto isso, as ORs ajustados foram 0,77 (IC95%: 0,64-0,92) e 0,80 (IC95%: 0,68-0,94), separadamente, para adultos com consumo eventual e diário de verduras para desenvolver uma PC única, comparado aos que relatavam consumo raro de verduras. Entretanto, não foi observada uma associação significativa entre consumo de frutas e PC. Entre a população chinesa com alto risco de DCV, o consumo de verduras frescas mostrou associação negativa com o risco de desenvolvimento de placa carotídea.

El objetivo de este estudio fue investigar la asociación del consumo de frutas y verduras con la placa carotídea (PC) y el grosor íntima-media carotídeo (GIMC), dos predictores de la aterosclerosis carotídea en adultos urbanos y rurales, con alto riesgo de desarrollar enfermedades cardiovasculares (ECV) en una región de China. Se identificaron, en este estudio transversal, a 11.392 adultos con alto riesgo de ECV dentro de una población general de 71.511, realizado entre noviembre de 2015 y mayo de 2016 en la provincia de Jiangsu. De estos 11.392 participantes en alto riesgo, la prevalencia de PC fue de un 36,7%. Las variables independientes, así como la frecuencia de consumo de verduras y fruta, se evaluaron mediante un cuestionario de frecuencia de comidas. Las variables de resultado, GIMC y PC, se midieron por un examen de ultrasonido. El análisis ANCOVA mostró que no existía asociación entre los valores GIMC y la frecuencia en el consumo de verduras y frutas. Los modelos de regresión logística multivariantes se introdujeron para examinar la asociación entre el consumo de verduras y frutas y la PC. Tras el ajuste para los factores potenciales de confusión, las ORs de haber tenido alguna PC para los participantes que ocasionalmente y diariamente consumían verduras fueron 0,67 (IC95%: 0,58-0,78) y 0,70 (IC95%: 0,62-0,79), respectivamente, comparadas con quienes raramente consumían verduras. Mientras que las ORs ajustadas fueron 0,77 (IC95%: 0,64-0,92) y 0,80 (IC95%: 0,68-0,94), separadamente, para los consumidores ocasionales y los consumidores diarios de verduras de desarrollar una única PC, en relación con sus contrapartes que raramente consumían verduras. No obstante, no se observó una asociación significativa entre el consumo de frutas y la PC. Entre la población con alto riesgo de ECV, el consumo de verdura fresca estuvo negativamente asociado con el riesgo de desarrollar PC.

Genetic Variants in Group-Specific Component (GC) Gene Are Associated with Breast Cancer Risk among Chinese Women.

The group-specific component (GC) gene, one of the vitamin D pathway genes, seems to play an important role in cancer development. A population-based breast cancer study including 818 cases and 935 controls in a Chinese population was carried out to evaluate the potential associations of four polymorphisms (rs16847024, rs17467825, rs2298850, and rs3755967) in the GC gene with risk of breast cancer. We detected three SNPs with statistically significant effects on breast cancer development after adjusting for age, menopausal status, body mass index (BMI), family history of breast cancer, income, waist circumference, and education (rs17467825: adjusted OR = 0.80, 95% CI = 0.65-0.99; rs2298850: adjusted OR = 0.80, 95% CI = 0.65-0.98; rs3755967: adjusted OR = 0.80, 95% CI = 0.65-0.98). Stratified analysis found that when an individual had a waist circumference <80 cm, rs17467825, rs2298850, and rs3755967 could markedly reduce the risk of breast cancer. Significant interactions between polymorphisms of rs2298850 and rs3755967 and waist circumference were also observed for breast cancer risk. Combined analysis revealed a significant association among the allele numbers of protective effects with decreased breast cancer risk (P trend=0.043). These results indicated that, in the GC gene, genetic mutations might be related to breast cancer susceptibility in Chinese women.

Adult weight change and the risk of pre- and postmenopausal breast cancer in the Chinese Wuxi Exposure and Breast Cancer Study.

PURPOSE: The accumulating evidence indicates that weight gain in adulthood is more predictive of breast cancer risk than absolute body weight. However, the relative impact of timing of weight gain in adulthood on breast cancer as well as other characteristics of the association between weight and breast cancer has not been well documented. METHODS: This population-based case-control study of breast cancer included 818 patients with newly diagnosed primary breast cancer and 935 residence and age-matched healthy controls. The body weight values at 18 years old, 1 year before diagnosis, and at menopause were obtained during in-person interviews. Unconditional logistic regression was used to estimate the effects of the weight change over adulthood on breast cancer risk. Linear mixed-effects regression was also applied as a secondary analysis. RESULTS: We found that the increased risk of breast cancer was associated with the weight gain in adulthood among postmenopausal women (OR 1.23; 95% CI 1.10-1.37 per 5 kg increase) but not in the premenopausal women. The risk associated with weight gain since menopause (OR 1.65; 95% CI 1.28-2.14 a 5-kg increase) was higher than that from age 18 to menopause (OR 1.14; 95% CI 1.02, 1.28 a 5-kg increase). The association tended to be stronger in those with higher waist circumference and who had never used hormone replacement therapy (HRT). Women who had never used HRT, the increased risk of breast cancer associated with weight gain was more consistent in leaner women at age 18 (BMI < 18.5) or at menopause (BMI < 24). CONCLUSIONS: Our findings indicated that weight gain has significant impact on postmenopausal breast cancer risk. The time periods of weight gain, central body fat, and HRT may affect the observed association, which should be further studied.

Age at menarche and age at natural menopause as predictors of glycemic control in type 2 diabetic patients.

OBJECTIVE: To investigate the influence of age at menarche (AM) and age at natural menopause (ANM) on glycemic control in patients with type 2 diabetes mellitus (T2DM). METHODS: A cross-sectional study was undertaken in Jiangsu, China. Logistic regression was used to evaluate the association between AM/ANM and glycemic control. RESULTS: 1195 (14.3%) premenopausal and 7149 (85.7%) postmenopausal women were included in this study. With the increase of AM per 1 year, patients had a low risk of uncontrolled FPG (≥7 mmol/L) and uncontrolled HbA1c (≥7%), as well as poor glycemic control (FPG ≥7 mmol/L and HbA1c ≥7%) after adjusting for age and BMI (model I, P < 0.05) with odds ratio (OR) 0.965, 0.978 and 0.962 respectively. Whereas after adjusting for age, BMI, education, duration of diabetes, smoking, drinking and antidiabetic treatment (model II) as well as further plus diabetic familial history and physical activity (model III), the association between AM and glycemic control was not significant (P > 0.05). Compared with premenopausal women, postmenopausal women had a low risk of uncontrolled FPG and uncontrolled HbA1c after adjusting for confounders in model II (P < 0.05). Furthermore, both patients with early ANM (<45 years) and late ANM (>55 years) had a high risk of uncontrolled HbA1c as well as poor glycemic control even adjusted for full confounders in model III (P < 0.05 for all). CONCLUSION: Early AM, early and late ANM were significantly associated with worse glycemic control. Ascertaining the AM and ANM in women with T2DM may help to identify the risk predisposed to worse glycemic control.

Interactions between RASA2, CADM1, HIF1AN gene polymorphisms and body fatness with breast cancer: a population-based case-control study in China.

Genome-wide association studies (GWAS) have indicated that gene polymorphisms in alleles of RAS p21 protein activator 2 (RASA2), cell adhesion molecule 1 (CADM1) and hypoxia inducible factor 1 alpha subunit inhibitor (HIF1AN) are associated with the risk of obesity. In this study, we explored the interactions between candidate SNPs of RASA2 (rs16851483), CADM1 (rs12286929) and HIF1AN (rs17094222) and body fatness for breast cancer risk. Unconditional logistic regression models were applied to measure the associations of related factors with breast cancer by odds ratios (ORs) and 95% confidence intervals (CIs). It was observed that cases had a statistically higher body mass index (BMI ≥ 28 kg/m2, OR = 1.77), waist circumference (WC ≥ 90cm, OR = 2.89) and waist-to-hip ratio (WHR ≥ 0.9, OR = 3.41) as compared to controls. Significant differences were also found in the genotype distributions of RASA2 rs16851483 T/T homozygote and CADM1 rs12286929 G/A heterozygote between cases and controls, with an OR of 1.68 (95% CI: 1.10-2.56) and 0.80 (95% CI: 0.64-0.99), respectively. Furthermore, significant interactions were observed between polymorphisms of three genes and body fatness for the risk of breast cancer based on both additive and multiplicative scales. These results of our study suggest that body fatness possibly plays an important role in the development of breast cancer and this risk might be modified by specific genotypes of some potential genes, especially for obese women in China.

The association of dietary pattern and breast cancer in Jiangsu, China: A population-based case-control study.

This study aims to examine the association of breast cancer with dietary patterns among Chinese women. A population-based case-control study was conducted in Jiangsu, China. Newly diagnosed primary breast cancer patients were recruited as cases (n = 818). Controls (n = 935), selected from the general population, were frequency matched to cases. A validated food frequency questionnaire was used to assess dietary intake. Dietary patterns were identified by factor analysis and multivariable odds ratios (OR) and 95% confidence intervals (CI) were estimated. Four dietary patterns were identified: salty, vegetarian, sweet and traditional Chinese. The traditional Chinese pattern was found to be robustly associated with a lower risk of breast cancer among both pre- and post-menopausal women (4th vs. 1st quartile: OR for pre- and post-menopausal women was 0.47 and 0.68, respectively). Women with high factor scores of the sweet pattern also showed a decreased risk of breast cancer (4th vs. 1st quartile: OR for pre- and post-menopausal women was 0.47 and 0.68, respectively). No marked association was observed between a vegetarian pattern or a salty pattern and breast cancer. These findings indicate that dietary patterns of the traditional Chinese and the sweet may favorably associate with the risk of breast cancer among Chinese women.

Application of the back-error propagation artificial neural network (BPANN) on genetic variants in the PPAR-γ and RXR-α gene and risk of metabolic syndrome in a Chinese Han population.

This study was aimed to explore the associations between the combined effects of several polymorphisms in the PPAR-γ and RXR-α gene and environmental factors with the risk of metabolic syndrome by back-error propagation artificial neural network (BPANN). We established the model based on data gathered from metabolic syndrome patients (n = 1012) and normal controls (n = 1069) by BPANN. Mean impact value (MIV) for each input variable was calculated and the sequence of factors was sorted according to their absolute MIVs. Generalized multifactor dimensionality reduction (GMDR) confirmed a joint effect of PPAR-γ and RXR-α based on the results from BPANN. By BPANN analysis, the sequences according to the importance of metabolic syndrome risk factors were in the order of body mass index (BMI), serum adiponectin, rs4240711, gender, rs4842194, family history of type 2 diabetes, rs2920502, physical activity, alcohol drinking, rs3856806, family history of hypertension, rs1045570, rs6537944, age, rs17817276, family history of hyperlipidemia, smoking, rs1801282 and rs3132291. However, no polymorphism was statistically significant in multiple logistic regression analysis. After controlling for environmental factors, A1, A2, B1 and B2 (rs4240711, rs4842194, rs2920502 and rs3856806) models were the best models (cross-validation consistency 10/10, P = 0.0107) with the GMDR method. In conclusion, the interaction of the PPAR-γ and RXR-α gene could play a role in susceptibility to metabolic syndrome. A more realistic model is obtained by using BPANN to screen out determinants of diseases of multiple etiologies like metabolic syndrome.

Association between PPAR-γ and RXR-α gene polymorphism and metabolic syndrome risk: a case-control study of a Chinese Han population.

BACKGROUND AND AIMS: Polymorphisms in peroxisome proliferator activated receptor-γ (PPAR-γ) and retinoid X receptor-α (RXR-α) gene may alter metabolic syndrome (MetS) risks by increasing or decreasing the human adiponectin promoter activity in cells. To test this statement, three potentially functional SNPs of PPAR-γ and four SNPs of RXR-α with minor allele frequency (MAF) ≥0.05 in the Chinese Han population were identified from NCBI dbSNPs database to evaluate their associations with MetS. METHODS: TaqMan assay was performed to test the genotypes in MetS patients (n = 901) and normal controls (n = 1009). Serum adiponectin concentration was measured by ELISA kit. RESULTS: The variant genotypes rs2920502CG and CG/CC, rs4240711GG and AG/GG, rs4842194CC and CT/CC, rs3132291CT, CC and CT/CC were associated with MetS. Furthermore, in the haplotype of PPAR-γ gene, compared with the most common haplotype GC, haplotype CC was associated with an increased risk of MetS (crude p = 0.017). In the haplotype of RXR-α gene, haplotype GCGC was associated with a significant protective effect for MetS [adjusted p = 0.002, OR (95% CI) = 0.718 (0.585-0.882)] compared with the most common haplotype GTAT. After taking smoking, alcohol consumption and physical activity as environmental adjustment factors into the analysis, the result showed A1 A2 A4 A5 A6 A7 B1 (rs3856806, rs2920502, rs180128, rs1045570, rs3132291, rs4240711, rs4842194) was the best model (cross-validation consistency 10/10, p = 0.0107). CONCLUSIONS: The present study suggested that the variant genotypes in PPAR-γ gene could increase the risk of MetS; however, genotypes in RXR-α gene could decrease the risk of MetS in a Chinese Han population.

Application of back propagation artificial neural network on genetic variants in adiponectin ADIPOQ, peroxisome proliferator-activated receptor-γ, and retinoid X receptor-α genes and type 2 diabetes risk in a Chinese Han population.

AIMS: Our study was designed to explore the applied characteristics of the back propagation artificial neural network (BPANN) on studying the genetic variants in adipnectin ADIPOQ, peroxisome proliferator-activated receptor (PPAR)-γ, and retinoid X receptor-α (RXR-α) genes and type 2 diabetes mellitus (T2DM) risks in a Chinese Han population. SUBJECTS AND METHODS: We used BPANN as the fitting model based on data gathered from T2DM patients (n=913) and normal controls (n=1,001). The mean impact value (MIV) for each input variables were calculated, and the sequence of the factors according to their absolute MIVs was sorted. RESULTS: The results from BPANN were compared with multiple logistic regression analysis, and the generalized multifactor dimensionality reduction (GMDR) method was used to calculate the joint effects of ADIPOQ, PPAR-γ, and RXR-α genes. By BPANN analysis, the sequence according to the importance of the T2DM risk factors was in the order of serum adiponectin level, rs3856806, rs7649121, hypertension, rs3821799, rs17827276, rs12495941, rs4240711, age, rs16861194, waist circumference, rs2241767, rs2920502, rs1063539, alcohol drinking, smoking, hyperlipoproteinemia, gender, rs3132291, T2DM family history, rs4842194, rs822394, rs1801282, rs1045570, rs16861205, rs6537944, body mass index, rs266729, and rs1801282. However, compared with multiple logistic regression analysis, only 11 factors were statistically significant. After overweight and obesity were taken as environment adjustment factors into the analysis, model A2 B4 C5 C6 C8 (rs3856806, rs4240711, rs7649121, rs3821799, rs12495941) was the best model (coefficient of variation consistency=10/10, P=0.0107) in the GMDR method. CONCLUSIONS: These results suggested the interactions of ADIPOQ, PPAR-γ, and RXR-α genes might play a role in susceptibility to T2DM. BPANN could be used to analyze the risk factors of diseases and provide more complicated relationships between inputs and outputs.