Epidemiological Interactions of Influenza and SARS-CoV-2 within a University Population During Omicron B.1.1.529 Outbreak

The COVID-19 Pandemic has prompted innovation and research to further understand not only SARS-CoV-2, but other respiratory viruses as well. Since the start of the pandemic there has been a lack in influenza collection and surveillance. In October 2021 the Life Sciences Testing Center at Northeastern University implemented the TaqPath COVID-19, Flu A, Flu B combo kit to test for multiple respiratory diseases among the Universitys population. During this time the SARS-CoV-2 variant of concern, Omicron B.1.1.529, became the dominant strain in the greater Boston area. During this time an inverse correlation in the detection of positive SARS-CoV-2 and Influenza A was observed. More data is needed to determine if this observed inverse correlation on positivity rate is linked to public health measures or biological mechanism within the immune system.

Mucosal antibody response to SARS-CoV-2 in paediatric and adult patients: a longitudinal study

Conjunctival and nasal mucosal antibody responses in thirty-four paediatric and forty-seven adult COVID-19 patients were measured. The mucosal antibody was IgA dominant. In the nasal epithelial lining fluid (NELF) of asymptomatic paediatric patients, SARS-CoV-2 spike protein 1 (S1) specific immunoglobulin A (IgA) was induced early. Their plasma S1-specific IgG levels were higher than symptomatic patients. More adult with mild disease had NELF S1-specific IgA than those with severe/critical illness. Within the first week of diagnosis, higher S1-specific antibodies in NELF and plasma and lower vial loads were detected in paediatric than adult patients with mild disease. The IgA and IgG levels correlated positively with the surrogate neutralization readout. The detectable NELF neutralizing S1-specific IgA in the first week after diagnosis correlated with a rapid decline in viral load. This study highlights the effect of nasal IgA in limiting the SARS-CoV-2 replication and provides complementary information to the serum antibody measurements.

Upper airway gene expression reveals a more robust innate and adaptive immune response to SARS-CoV-2 in children compared with older adults

Unlike other respiratory viruses, SARS-CoV-2 disproportionately causes severe disease in older adults and only rarely in children. To investigate whether differences in the upper airway immune response could contribute to this disparity, we compared nasopharyngeal gene expression in 83 children (<19-years-old; 38 with SARS-CoV-2, 11 with other respiratory viruses, 34 with no virus) and 154 adults (>40-years-old; 45 with SARS-CoV-2, 28 with other respiratory viruses, 81 with no virus). Expression of interferon-stimulated genes (ISGs) was robustly activated in both children and adults with SARS-CoV-2 compared to the respective non-viral groups, with only relatively subtle distinctions. Children, however, demonstrated markedly greater upregulation of pathways related to B cell and T cell activation and proinflammatory cytokine signaling, including TNF, IFN{gamma}, IL-2 and IL-4 production. Cell type deconvolution confirmed greater recruitment of B cells, and to a lesser degree macrophages, to the upper airway of children. Only children exhibited a decrease in proportions of ciliated cells, the primary target of SARS-CoV-2, upon infection with the virus. These findings demonstrate that children elicit a more robust innate and adaptive immune response to SARS-CoV-2 infection in the upper airway that likely contributes to their protection from severe disease in the lower airway.

Study on the mucosal and serological immune response to the Novel Coronavirus (SARS-CoV-2) vaccine

Vaccines that elicit mucosal immune responses against SARS-CoV-2 could potentially be of exceptional importance in providing first line defense at the site of viral entry. The serological antibody response induced by SARS-CoV-2 vaccines have already been well characterized. In order to understand the mucosal immune response profiles of SARS-CoV-2 vaccines, we examined both the mucosal and systemic responses of subjects vaccinated by two different vaccination platforms: mRNA (Comirnaty) and inactivated virus (CoronaVac). Serial nasal epithelial lining fluid (NELF) and peripheral blood samples were collected in ten subjects who had received CoronaVac and thirty-two subjects who had received Comirnaty. We quantified IgA and IgG specific to SARS-CoV-2 S1 protein by ELISA in NELF and plasma samples. The neutralization effect of these two sample types were evaluated by surrogate ACE-SARS-CoV-2 Spike protein ELISA. Only Comirnaty induced nasal SARS-CoV-2 S1 protein-specific (S1-specific) IgA and IgG responses, which were evident as early as on 14{+/-}2 days after the first dose. The NELF samples of 72% of subjects became IgA+IgG+, while in 62.5% of subjects the samples were neutralizing by 7{+/-}2 days after the second dose. In 45% of the subjects their NELF remained neutralizing 50 days after the booster of Comirnaty. In plasma, 91% and 100% Comirnaty subjects possessed S1-specific IgA+IgG+ on 14{+/-}2 days after the first dose and 7{+/-}2 days after booster, respectively. The plasma collected on 7{+/-}2 days after booster was 100% neutralizing. The induction of S1-specific antibody by CoronaVac was IgG dominant, and 70% of the subjects possessed S1-specific IgG by 7{+/-}2 days after booster and were all neutralizing. This study reveals that Comirnaty is able to induce S1-specific IgA and IgG response with neutralizing activity in the nasal mucosa in addition to a consistent systemic response. The clinical implications and the biological mechanism of an additional nasal immune response induced by vaccines such as Comirnaty warrant further investigation. One Sentence SummarymRNA vaccine (CoronaVac) elicits mucosal IgA and IgG in the nasal epithelial lining fluid together with ELISA-detected anti-wild-type spike neutralizing antibodies as early as day 14 post vaccination.

The impact of COVID-19 pandemic on influenza transmission: molecular and epidemiological evidence

To quantify the impact of COVID-19-related control measures on the spread of human influenza virus, we analyzed case numbers, viral molecular sequences, personal behavior data, and policy stringency data from various countries, and found consistent evidence of decrease in influenza incidence after the emergence of COVID-19. Article SummaryWe quantify a noticeable decrease in H1N1 and H3N2 cases and genetic diversity in selected countries since the onset of the COVID-19 pandemic.

Virologic features of SARS-CoV-2 infection in children

BackgroundData on pediatric COVID-19 has lagged behind adults throughout the pandemic. An understanding of SARS-CoV-2 viral dynamics in children would enable data-driven public health guidance. MethodsRespiratory swabs were collected from children with COVID-19. Viral load was quantified by RT-PCR; viral culture was assessed by direct observation of cytopathic effects and semiquantitative viral titers. Correlations with age, symptom duration, and disease severity were analyzed. SARS-CoV-2 whole genome sequences were compared with contemporaneous sequences. Results110 children with COVID-19 (median age 10 years, range 2 weeks-21 years) were included in this study. Age did not impact SARS-CoV-2 viral load. Children were most infectious within the first five days of illness, and severe disease did not correlate with increased viral loads. Pediatric SARS-CoV-2 sequences were representative of those in the community and novel variants were identified. ConclusionsSymptomatic and asymptomatic children can carry high quantities of live, replicating SARS-CoV-2, creating a potential reservoir for transmission and evolution of genetic variants. As guidance around social distancing and masking evolves following vaccine uptake in older populations, a clear understanding of SARS-CoV-2 infection dynamics in children is critical for rational development of public health policies and vaccination strategies to mitigate the impact of COVID-19.

Estimation of secondary household attack rates for emergent SARS-CoV-2 variants detected by genomic surveillance at a community-based testing site in San Francisco

BackgroundSequencing of the SARS-CoV-2 viral genome from patient samples is an important epidemiological tool for monitoring and responding to the pandemic, including the emergence of new mutations in specific communities. MethodsSARS-CoV-2 genomic sequences were generated from positive samples collected, along with epidemiological metadata, at a walk-up, rapid testing site in the Mission District of San Francisco, California during November 22-December 2, 2020 and January 10-29, 2021. Secondary household attack rates and mean sample viral load were estimated and compared across observed variants. ResultsA total of 12,124 tests were performed yielding 1,099 positives. From these, 811 high quality genomes were generated. Certain viral lineages bearing spike mutations, defined in part by L452R, S13I, and W152C, comprised 54.9% of the total sequences from January, compared to 15.7% in November. Household contacts exposed to "West Coast" variants were at higher risk of infection compared to household contacts exposed to lineages lacking these variants (0.357 vs 0.294, RR=1.29; 95% CI:1.01-1.64). The reproductive number was estimated to be modestly higher than other lineages spreading in California during the second half of 2020. Viral loads were similar among persons infected with West Coast versus non-West Coast strains, as was the proportion of individuals with symptoms (60.9% vs 64.1%). ConclusionsThe increase in prevalence, relative household attack rates, and reproductive number are consistent with a modest transmissibility increase of the West Coast variants; however, additional laboratory and epidemiological studies are required to better understand differences between these variants. SummaryWe observed a growing prevalence and elevated attack rate for "West Coast" SARS-CoV-2 variants in a community testing setting in San Francisco during January 2021, suggesting its modestly higher transmissibility.

How much do superspreaders matter? Epidemic dynamics in inhomogeneous populations

A variant of the SIR model for an inhomogeneous population is introduced in order to account for the effect of variability in susceptibility and infectiousness across a population. An initial formulation of this dynamics leads to infinitely many differential equations. Our model, however, can be reduced to a single first-order one-dimensional differential equation. Using this approach, we provide quantitative solutions for different distributions. In particular, we use GPS data from [~] 107 cellphones to determine an empirical distribution of the number of individual contacts and use this to infer a possible distribution of susceptibility and infectivity. We quantify the effect of superspreaders on the early growth rate [R]0 of the infection and on the final epidemic size, the total number of people who are ever infected. We discuss the features of the distribution that contribute most to the dynamics of the infection.

Application of Next Generation Sequencing in Laboratory Medicine

The rapid development of next-generation sequencing (NGS) technology, including advances in sequencing chemistry, sequencing technologies, bioinformatics, and data interpretation, has facilitated its wide clinical application in precision medicine. This review describes current sequencing technologies, including short- and long-read sequencing technologies, and highlights the clinical application of NGS in inherited diseases, oncology, and infectious diseases. We review NGS approaches and clinical diagnosis for constitutional disorders; summarize the application of U.S. Food and Drug Administration-approved NGS panels, cancer biomarkers, minimal residual disease, and liquid biopsy in clinical oncology; and consider epidemiological surveillance, identification of pathogens, and the importance of host microbiome in infectious diseases. Finally, we discuss the challenges and future perspectives of clinical NGS tests.

SARS-CoV-2 detection by nasal strips: a superior tool for surveillance of pediatric populations.

BackgroundDeep throat saliva (DTS) and pooled nasopharyngeal swab and throat swab (NPSTS) are utilized for viral detection. DTS is challenging for children. Swabbing the respiratory mucosa requires trained personnel and may trigger sneezing and coughing, which generate droplets. A reliable, simple and safe sampling method applicable to a wide age range is required for community-based surveillance. MethodsWe introduced nasal strip as an easy and low-risk collection method. Asymptomatic and symptomatic SARS-CoV-2 infected patients (n = 38) were recruited. Nasal epithelial lining fluid (NELF) (n = 43) strip paired with nasal swab (n = 13) were collected by a healthcare worker to compare with NPSTS (n = 21) or DTS (n =22) collected within 24 hours as reference. All samples were subjected to viral RNA quantitation by real-time PCR targeting the nucleoprotein gene. ResultsComparable Ct values were observed between paired nasal strip and nasal swab samples. The agreement between nasal strip samples and NPSTS was 94.44% and 100% for NPSTS positive and negative samples. Higher viral RNA concentration was detected in nasal strips than DTS samples. False-negative results were recorded in six DTS specimens, of which four were from children. Storage at room temperature up to 72 (n = 3) hours did not affect diagnostic yield of nasal strips. ConclusionsNasal strip is a reliable and non-invasive sampling method for SARS-CoV-2 detection, and viral detection remains stable for at least 72 hours. It can be used as an alternative tool for community-based surveillance.

Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2

We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.

Using viral genomics to estimate undetected infections and extent of superspreading events for COVID-19

Asymptomatic infections and limited testing capacity have led to under-reporting of SARS-CoV-2 cases. This has hampered the ability to ascertain true infection numbers, evaluate the effectiveness of surveillance strategies, determine transmission dynamics, and estimate reproductive numbers. Leveraging both viral genomic and time series case data offers methods to estimate these parameters. Using a Bayesian inference framework to fit a branching process model to viral phylogeny and time series case data, we estimated time-varying reproductive numbers and their variance, the total numbers of infected individuals, the probability of case detection over time, and the estimated time to detection of an outbreak for 12 locations in Europe, China, and the United States. The median percentage of undetected infections ranged from 13% in New York to 92% in Shanghai, China, with the length of local transmission prior to two cases being detected ranging from 11 days (95% CI: 4-21) in California to 37 days (9-100) in Minnesota. The probability of detection was as low as 1% at the start of local epidemics, increasing as the number of reported cases increased exponentially. The precision of estimates increased with the number of full-length viral genomes in a location. The viral phylogeny was informative of the variance in the reproductive number with the 32% most infectious individuals contributing 80% of total transmission events. This is the first study that incorporates both the viral genomes and time series case data in the estimation of undetected COVID-19 infections. Our findings suggest the presence of undetected infections broadly and that superspreading events are contributing less to observed dynamics than during the SARS epidemic in 2003. This genomics-informed modeling approach could estimate in near real-time critical surveillance metrics to inform ongoing COVID-19 response efforts. FundingAWS provided computational credit via the Diagnostic Development Initiative.

Clinical features, diagnostics, and outcomes of patients presenting with acute respiratory illness: a comparison of patients with and without COVID-19

BackgroundEmerging data on the clinical presentation, diagnostics, and outcomes of patients with COVID-19 have largely been presented as case series. Few studies have compared these clinical features and outcomes of COVID-19 to other acute respiratory illnesses. MethodsWe examined all patients presenting to an emergency department in San Francisco, California between February 3 and March 31, 2020 with an acute respiratory illness who were tested for SARS-CoV-2. We determined COVID-19 status by PCR and metagenomic next generation sequencing (mNGS). We compared demographics, comorbidities, symptoms, vital signs, and laboratory results including viral diagnostics using PCR and mNGS. Among those hospitalized, we determined differences in treatment (antibiotics, antivirals, respiratory support) and outcomes (ICU admission, ICU interventions, acute respiratory distress syndrome, cardiac injury). FindingsIn a cohort of 316 patients, 33 (10%) tested positive for SARS-CoV-2; 31 patients, all without COVID-19, tested positive for another respiratory virus (16%). Among patients with additional viral testing, no co-infections with SARS-CoV-2 were identified by PCR or mNGS. Patients with COVID-19 reported longer symptoms duration (median 7 vs. 3 days) and were more likely to report fever (82% vs. 44%) fatigue (85% vs. 50%) and myalgias (61% vs 27%); p<0.001 for all comparisons. Lymphopenia (55% vs 34%, p=0.018) and bilateral opacities on initial chest radiograph (55% vs. 24%, p=0.001) were more common in patients with COVID-19. Patients with COVID-19 were more often hospitalized (79% vs. 56%, p=0.014). Of 186 hospitalized patients, patients with COVID-19 had longer hospitalizations (median 10.7d vs. 4.7d, p<0.001) and were more likely to develop ARDS (23% vs. 3%, p<0.001). Most comorbidities, home medications, signs and symptoms, vital signs, laboratory results, treatment, and outcomes did not differ by COVID-19 status. InterpretationWhile we found differences in clinical features of COVID-19 compared to other acute respiratory illnesses, there was significant overlap in presentation and comorbidities. Patients with COVID-19 were more likely to be admitted to the hospital, have longer hospitalizations and develop ARDS, and were unlikely to have co-existent viral infections. These findings enhance understanding of the clinical characteristics of COVID-19 in comparison to other acute respiratory illnesses.

Impact assessment of non-pharmaceutical interventions against COVID-19 and influenza in Hong Kong: an observational study

BackgroundA range of public health measures have been implemented to delay and reduce local transmission of COVID-19 in Hong Kong, and there have been major changes in behaviours of the general public. We examined the effect of these interventions and behavioral changes on the incidence of COVID-19 as well as on influenza virus infections which may share some aspects of transmission dynamics with COVID-19. MethodsWe reviewed policy interventions and measured changes in population behaviours through two telephone surveys, on January 20-23 and February 11-14. We analysed data on laboratory-confirmed COVID-19 cases, influenza surveillance data in outpatients of all ages, and influenza hospitalisations in children. We estimated the daily effective reproduction number (Rt), for COVID-19 and influenza A(H1N1). FindingsCOVID-19 transmissibility has remained at or below 1, indicating successful containment to date. Influenza transmission declined substantially after the implementation of social distancing measures and changes in population behaviours in late January, with a 44% (95% confidence interval, CI: 34% to 53%) reduction in transmissibility in the community, and a 33% (95% CI: 24% to 43%) reduction in transmissibility based on paediatric hospitalization rates. In the two surveys we estimated that 74.5% and 97.5% of the general adult population wore masks when going out, and 61.3% and 90.2% avoided going to crowded places, respectively. ImplicationsContainment measures, social distancing measures and changes in population behaviour have successfully prevented spread of COVID-19. The social distancing measures and behavioural changes led to a substantial reduction in influenza transmission in early February 2020. However, it may be challenging to avoid fatigue and sustain these measures and population behaviours as COVID-19 continues to spread globally. FundingHealth and Medical Research Fund, Hong Kong

Data science in large cohort studies / 中华流行病学杂志

Large cohort study gained its popularity in biomedical research and demonstrated its application in exploring disease etiology and pathogenesis, improving the prognosis of disease, as well as reducing the burden of diseases. Data science is an interdisciplinary field that uses scientific methods from computer science and statistics to extract insights or knowledge from data in a specific domain. The results from the combination of the two would provide new evidence for developing the strategies and measures on disease prevention and control. This review included a brief introduction of data science, descriptions on characteristics of large cohort data according to the development of the study design, and application of data science at each stage of a large cohort study, as well as prospected the application of data science in the future large cohort studies.

Interpretation for the group standards in data management for large population-based cohorts / 中华流行病学杂志

Precision medicine became the key strategy in development priority of science and technology in China. The large population-based cohorts become valuable resources in preventing and treating major diseases in the population, which can contribute scientific evidence for personalized treatment and precise prevention. The fundamental question of the achievements above, therefore, is how to construct a large population-based cohort in a standardized way. The Chinese Preventive Medicine Association co-ordinated experienced researchers from Peking University and other well-known institutes to write up two group standards Technical specification of data processing for large population-based cohort study (T/CPMA 001-2018) and Technical specification of data security for large population-based cohort study (T/CPMA 002-2018), on data management. The standards are drafted with principles of emphasizing their scientific, normative, feasible, and generalizable nature. In these two standards, the key principles are proposed, and technical specifications are recommended in data standardization, cleansing, quality control, data integration, data privacy protection, and database security and stability management in large cohort studies. The standards aim to guide the large population-based cohorts that have been or intended to be established in China, including national cohorts, regional population cohorts, and special population cohorts, hence, to improve domestic scientific research level and the international influence, and to support decision-making and practice of disease prevention and control.

Study on genetic structure differences and adjustment strategies in different areas of China / 中华流行病学杂志

Objective: To describe the genetic structure of populations in different areas of China, and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies. Methods: By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB), we performed principal components analysis to extract the first and second principal components of the samples for the component two-dimensional diagram generation, and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China. Based on the CKB cohort data, a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated; and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated. Results: There were significant genetic structure differences in different areas of China. Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area. The first principal component corresponds to the latitude of different areas, and the second principal component corresponds to the longitude of different areas. The generated simulation data showed high false positive rate (λ=1.16), even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed, λ could not be effectively controlled (λ>1.05); while, by using a mixed linear model adjusting for the kinship matrix, λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ=0.99). Conclusions: There were large differences in genetic structure among populations in different areas of China. In molecular epidemiology studies, bias caused by population genetic structure needs to be carefully treated. For large cohort data with complex genetic structure and extensive kinship, it is necessary to use a mixed linear model for association analysis.

Relationship between educational level and long-term changes of body weight and waist circumference in adults in China / 中华流行病学杂志

Objective: To evaluate the association of educational level with anthropometric measurements at different adult stages and their long-term changes in adults who participated in the second re-survey of China Kadoorie Biobank (CKB). Methods: The present study excluded participants who were aged >65 years, with incomplete or extreme measurement values, or with major chronic diseases at baseline survey or re-survey. The weight at age 25 years was self-reported. Body height, body weight and waist circumference at baseline survey (2004-2008) and re-survey (2013-2014) were analyzed. Results: The present study included 3 427 men and 6 320 women. Both body weight and waist circumference (WC) increased with age. From age 25 years to baseline survey (mean age 45.2±6.5), the mean weight change per 5-year was (1.70±2.63) kg for men and (1.27±2.10) kg for women. From baseline survey to re-survey (53.2±6.5), the mean changes per 5-year for body weight were (1.12±2.61) kg for men and (0.90±2.54) kg for women; and that for WC was (3.20±3.79) cm for men and (3.83±3.85) cm for women. Among women, low educational level was consistently associated with higher body mass index (BMI) and WC at age 25 years, baseline survey and re-survey. Among men, low educational level was associated with higher BMI at age 25 years. At baseline survey and re-survey, the educational level in men was not statistically associated with BMI; but men who completed junior or senior high school showed slight higher WC and increase of WC from baseline survey to re-survey than other male participants. Conclusions: Body weight and WC increased with age for both men and women. The associations of educational level with BMI and WC were different between men and women.

Prevalence of 'healthy lifestyle' in Chinese adults / 中华流行病学杂志

Objective: To examine the prevalence of 'healthy lifestyle' from data extracted from the China Kadoorie Biobank (CKB) of 0.5 million adults from ten areas across China. Methods: After excluding participants with self-reported histories of coronary heart disease, stroke or cancer, a total of 487 198 participants at baseline (2004-2008) and 22 604 participants at second survey (2013- 2014), were included for analysis. 'Healthy lifestyle' was defined as haing the following characteristics: a) never smoking or having stopped smoking for reasons other than illness; b) alcohol drinking <25 g/day (men)/<15 g/day (women); c) diet rich in vegetables, fruits, legumes and fish, but low in red meat; d) upper quarter of the physical activity level; e) body mass index of 18.5-23.9 kg/m(2) and waist circumstance <85 cm (men)/80 cm (women). We calculated the healthy lifestyle scores (HLS) by counting the number of all the healthy lifestyle factors, with a range from 0 to 6. Results: At baseline, prevalence rates of the above five healthy lifestyles (except physical activity) were 70.6%, 92.6%, 8.7%, 52.6% and 59.0%, respectively, with the mean HLS being 3.1±1.2. Most participants (81.4%) had2-4 healthy components, while only 0.7% (0.2% in men and 1.0% in women) of all the participants had all six healthy lifestyles. Participants who were women, at younger age, with more schooling and rural residents, were more likely to adhere to the healthy lifestyle. After ten years, the mean HLS showed a slight decrease. Conclusion: The prevalence of optimal lifestyles in Chinese adults appeared extremely low. Levels of 'healthy lifestyle' varied greatly among those populations with different socio-demographic characteristics across the ten areas in China.

Impact of menarche age on the near-term and long-term obesity of adult females / 中华流行病学杂志

Objective: To study the relationship between the age of menarche and the near-term/long-term obesity in adult women. Methods: We analyzed the baseline data of 30 895 women with complete data on menarche and body measurement that was from the China Kadoorie Biobank (CKB) study from 2004 to 2008. The age of menarche was divided into three groups: ≤12, 13-16 and ≥17 years old. Prematurity was set at age ≤12 years. Multivariate logistic regression was used to analyze the effects of menarche age on the near/long-term obesity in female adults. Results: The average menarche age of respondent appeared as (15.64±1.92) years old, with prematurity number as 1 421, accounting for 4.6% of the total numbers. Regarding the postponing of dates of birth, the age of menarche in women showed an advancing tendency. Among all the adult women under study, 803 developed near-term obesity, with the prevalence as 2.6%, while the number of long-term obesity was 3 738, accounting for 12.1%. Refining factors of age, lifestyle, menopausal status, hypertension and diabetes showed that the menarche age was related to the risks of both short-term and long-term obesity in women and the ORs (95%CI) were 2.45 (1.74-3.45) and 1.99 (1.69-2.34), respectively. There was no multiplicative interaction shown between the menarche age and menopausal status on long-term obesity (P=0.324). Conclusion: Premature menarche appeared a risk factor for near-term/long-term obesity in adult females.