Multimorbidity, individuals suffering from two or more chronic diseases, has become a major health challenge worldwide, especially in populous and prosperous cities, where studies of this phenomenon in China are limited. We examined the prevalence, trends, patterns, and associated factors of multimorbidity from 2009 to 2018 among community-dwelling adults in Guangzhou, China. We conducted serial cross-sectional surveys for chronic diseases in Guangzhou, China, in 2009, 2013, and 2018. General and stratified prevalence were standardized using demographic data. Multivariable logistic regression and hierarchical cluster analysis were applied to identify associated factors and to assess the correlations and patterns of multimorbidity, respectively. This study included 23,284 adults aged 18 and over in 2009, 18,551 in 2013, and 15,727 in 2018. The standardized prevalence of multimorbidity increased substantially, with 12.69% (95% CI: 10.45-15.33) in 2009, 25.44% (95% CI: 23.47-27.52) in 2013, and 35.13% (95% CI:32.64-37.70) in 2018 (P for trend <0.001). The highest bi- and triple-conditions of multimorbidity were dyslipidemia (DP) and overweight or obesity (OO) (12.54%, 95% CI: 11.68-13.46), and DP, OO, and Hypertension (HT) (3.99%, 95% CI: 3.47-4.58) in 2018. From 2009 to 2018, (1) The majority of multimorbidity patterns showed a high prevalence; (2) The percentage of participants with only one chronic condition was found lower, while the percentage with multiple conditions was higher. The prevalence of chronic disease multimorbidity in Guangzhou China, has increased substantially among adults. Effective policies targeting multimorbidity are urgently needed, especially for the health management of primary medical institutions.

Exposure to high levels of estrogen is considered an important risk factor for susceptibility to breast cancer. Common polymorphisms in genes that affect estrogen levels may be associated with breast cancer risk, but no comprehensive study has been performed among Han Chinese women. In the present study, 32 single-nucleotide polymorphisms (SNPs) in estrogen-related genes were genotyped using the MassARRAY IPLEX platform in 1076 Han Chinese women. Genotypic and allelic frequencies were compared between case and control groups. Unconditional logistic regression was used to assess the effects of SNPs on breast cancer risk. Associations were also evaluated for breast cancer subtypes stratified by estrogen receptor (ER) and progesterone receptor (PR) status. Case-control analysis showed a significant relation between heterozygous genotypes of rs700519 and rs2069522 and breast cancer risk (OR = 0.723, 95% CI = 0.541–0.965, p = 0.028 and OR = 1.500, 95% CI = 1.078–2.087, p = 0.016, respectively). Subgroup comparisons revealed that rs2446405 and rs17268974 were related to ER status, and rs130021 was associated with PR status. Our findings suggest that rs700519 and rs2069522 are associated with susceptibility to breast cancer among the Han Chinese population and have a cumulative effect with three other identified SNPs. Further genetic and functional studies are needed to identify additional SNPs, and to elucidate the underlying molecular mechanisms.

Exposure to endogenous sex hormones has been reported as a risk factor for breast cancer. The CYP11A1 gene encodes the key enzyme that catalyzes the initial and rate-limiting step in steroid hormone synthesis. In this study, the associations between single nucleotide polymorphisms (SNPs) in CYP11A1 and breast cancer susceptibility were examined. Six SNPs in CYP11A1 were genotyped using the MassARRAY IPLEX platform in 530 breast cancer patients and 546 healthy controls. Association analyses based on a χ² test and binary logistic regression were performed to determine the odds ratio (OR) and 95% confidence interval (95% CI) for each SNP. Two loci (rs2959008 and rs2279357) showed evidence of associations with breast cancer risk. The variant genotype C/T-C/C of rs2959008 was significantly associated with a decreased risk (age-adjusted OR, 0.75; 95% CI, 0.58–0.96; P = 0.023) compared with the wild-type TT. However, the homozygous TT variant of rs2279357 exhibited increased susceptibility to breast cancer (age-adjusted OR, 1.44; 95% CI, 1.05–1.98; P = 0.022). The locus rs2959003 also showed an appreciable effect, but no associations were observed for three other SNPs. Our results suggest that polymorphisms of CYP11A1 are related to breast cancer susceptibility in Han Chinese women of South China.

Liquid biopsy through the detection of circulating tumor DNA (ctDNA) has potential advantages in cancer monitoring and prediction. However, most previous studies in this area were performed with a few hotspot genes, single time point detection, or insufficient sequencing depth. In this study, we performed targeted next-generation sequencing (NGS) with a customized panel in metastatic breast cancer (MBC) patients. Fifty-four plasma samples were taken before chemotherapy and after the third course of treatment for detection and analysis. Paired lymphocytes were also included to eliminate clonal hematopoiesis (CH)-related alternatives. A total of 1182 nonsynonymous mutations in 419 genes were identified. More ctDNA mutations were detected in patients with tumors > 3 cm (p = 0.035) and HER2(−) patients (p = 0.029). For a single gene, the distribution of ctDNA mutations was also correlated with clinical characteristics. Multivariate regression analysis revealed that HER2 status was significantly associated with mutation burden (OR 0.02, 95% CI 0–0.62, p = 0.025). The profiles of ctDNA mutations exhibited marked discrepancies between two time points, and baseline ctDNA was more sensitive and specific than that after chemotherapy. Finally, elevated ctDNA mutation level was positively correlated with poor survival (p < 0.001). Mutations in ctDNA could serve as a potential biomarker for the evaluation, prediction, and clinical management guidance of MBC patients with chemotherapy.

Background: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors. Methods: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition. Results: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = −0.25) or diabetes (RERI = −0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = −0.84) or dyslipidemia (RERI = −0.09) could lower the risk of obesity. Conclusions: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.

Background: Optimizing nutritional care for people with multimorbidity requires effective and feasible tools for early risk identification. This study aimed to investigate the associations of conicity index (C-index) and body roundness index (BRI) with multimorbidity among adults in Guangzhou, and to explore their potential utility in identifying individuals who may benefit from prioritized nutritional assessment. Methods: Based on the Fourth Adult Chronic Disease and Risk Factor Surveillance Program in Guangzhou, a total of 15,532 adults were recruited in this cross-sectional study. Multiple logistic regression analysis, restricted cubic spline (RCS) analysis and receiver operating characteristic curve (ROC) analysis with DeLong’s test were performed. Results: The prevalence of multimorbidity was 38.95%. Higher C-index and BRI quartiles were significantly associated with increased multimorbidity risk. Compared with the lowest quartile, the adjusted OR for the highest C-index quartile was 1.98 (95% CI: 1.78–2.21), and for the highest BRI quartile it was 3.05 (95% CI: 2.74–3.41). A dose–response relationship was observed (p < 0.001). BRI showed statistically significantly higher discriminative ability relative to traditional anthropometric indices, though its overall discriminative performance was modest (AUC = 0.678). Conclusions: C-index and BRI are strongly and positively associated with multimorbidity. These simple, non-invasive indices may support community-based risk stratification and help identify individuals who warrant further clinical and nutritional assessment.