OBJECTIVES

The prevalence of metabolic syndrome among Filipino adults was found to be 12-19%. Diet has been one risk factor targeted to prevent complications. The association of each macronutrient component with metabolic syndrome remains unclear. There is no Philippine data on macronutrient intake and metabolic syndrome, thus, the primary objective of this study is to determine the association of food intake with metabolic syndrome among Filipino adults.

METHODS

This study utilized a cross-sectional design. Data were taken from the results of the 8th National Nutrition and Health Survey (NNHeS). Filipino adults from different regions who consented to participate and with complete anthropometric, biochemical and food recall data were included in this study.

RESULTS

There were 8,056 adults included in the study. The prevalence of metabolic syndrome was 32%. Multivariate analysis showed that increased total protein intake (OR 1.391) and increased daily consumption of meat and poultry (OR 1.397) were associated with increased risk for metabolic syndrome. On the other hand, decreased vegetable intake was associated with increased risk for metabolic syndrome, as well as higher socioeconomic status, female sex, and old age.

CONCLUSION

ncreased total protein intake and daily consumptions of meat, poultry, and decreased vegetable intake are associated with an increased risk for metabolic syndrome.

Human ; Male ; Female ; World Health Organization ; Metabolic Syndrome ; Health Surveys ; Economics ; Multivariate Analysis ; Female

OBJECTIVES

A growing body of evidence points to a positive association between periodontitis and
various systemic diseases, including cardiovascular diseases (CVD), hypertension, and rheumatoid arthritis. However,
there is limited data on the prevalence and odds of having systemic conditions among Filipino periodontal patients.
Thus, this study aimed to determine the association of periodontal disease with systemic conditions among Filipino
patients at a university dental clinic.

METHODS

The periodontal and medical charts of all patients who underwent periodontal consult at a university
dental clinic within two academic years were reviewed. Periodontal diagnoses which had originally been assigned
using the 1999 classification of periodontal diseases were reclassified based on the 2018 European Federation
of Periodontology-American Academy of Periodontology classification. Listed medical conditions in the patients’
charts were self-reported. The prevalence of various systemic conditions in 715 periodontitis cases was compared
to that of 834 control patients without periodontitis. Fisher’s exact test was performed to evaluate the difference
in the prevalence of comorbidities between groups, while adjusted odds ratios (AOR) were computed using logistic
regression analysis, accounting for age, sex, educational attainment, and smoking status.

RESULTS

The prevalence of having at least one systemic condition was significantly higher among periodontitis patients
(44.5%) compared to non-periodontitis patients (36.3%). Compared to controls, a significantly higher number of
periodontitis cases had two systemic comorbidities (P=0.001). The prevalence of hypertension (18.6% versus 5.04%),
CVD including hypertension (20.42% versus 6.95%), arthritis (9.37% versus 3.0%), and diabetes mellitus (5.73% versus
0.84%) were all significantly higher in patients with periodontitis compared to non-periodontitis controls.
The odds of having CVD (AOR=1.81), hypertension (AOR=2.14) and diabetes (AOR=3.05) were higher in periodontitis cases. Meanwhile, the prevalence of asthma (9.23% versus 5.31%), respiratory diseases including asthma (12.95% versus 8.25%), and allergies (18.82% versus 13.71%) were significantly higher in non- periodontitis patients compared to periodontitis cases.

CONCLUSION

Periodontitis patients were more likely to present with CVD, hypertension, and diabetes mellitus. On the other hand, no association was found between periodontitis and respiratory diseases, as well as between periodontitis and asthma.

Human ; Male ; Female ; Adolescent: 13-18 Yrs Old ; Young Adult: 19-24 Yrs Old ; Adult: 25-44 Yrs Old ; Middle Aged: 45-64 Yrs Old ; Aged: 65-79 Yrs Old ; Regression (psychology) ; Respiratory Tract Diseases ; Regression Analysis ; Periodontal Diseases ; Cardiovascular Diseases

Academic publishing is at a critical juncture. The challenges faced by the academics are mired in controversy. Among theseare three hotly debated concerns. First is the issue of whether technological innovations such as artificial intelligence (AI)improves research efficiency or if its use sacrifices research integrity.Another is the controversy between paywall publishingand open access. Lastly, adapting an appropriate business model for sustainability is a contentious issue and the choice betweena commercial or a university-based publishing platform is a difficult one.

Traditional models of scientific investigation relied on tedious intellectual calisthenics in all aspects of research —identifying research gaps, reviewing of published literature, devising valid methodology, collecting data, analysing results, and,finally, drawing conclusions. With the advent of powerful tools employing artificial intelligence, these heavy tasks are efficientlycarried out. The dilemma lies in determining which parts of the work can be attributed to the authors and which are ascribedto the output of large language models (LLMs) and other automated assistance employed.Despite requiring adequate vettingby experts of these AI-aided output, many in the scientific community still question these methods. Can research employingAI be considered honest work? Will full disclosure answer doubts as to the integrity of the scientific work?

Indeed, LLMs just gather information that is already out there, albeit more efficiently. After all, science progresses bystanding on the shoulder of giants. AI makes such work comprehensive and efficient. Standing on those proverbial shoulders,however, require access to prior work, hence our next challenge in academic publishing--open access versus paid access.Paywalls limit the benefits of valuable research to institutions and universities with the capacity to pay. Excluded from these arethose from low resourced countries, with nations from the global south being affected disproportionately. Additionally, whilenumerous authors appreciate the features of open access as it improves their impact and visibility, many feel unduly burdenedsince the cost of publishing in this format is passed on to them.

This brings us to our third issue: who bears the cost of academic publishing? Indeed, it is a lucrative industry, generatingan annual revenue of US$19 billion and an estimated 40 percent profit margin. Many, however, find fault in this businessmodel as concerns about the profit motives of the commercial publishers far overshadow their sustainability goals.

How do we navigate this landscape of controversies? We, at the ACTA, as part of the community of scholars, would needto clarify our mission. Our goals for this publication should be consistent with our values. These values, such as scientific rigor,integrity, and accountability, should be reflected in our policies. We should be cognizant of the role we play in national scientificdiscourse while we endeavor to make an impact in the global scene. We are accountable to our stakeholders — nurturingearly career scholars, supplying evidence to health policymakers, and being accountable to those who provide resources tosustain us. This stewardship is essential so that ACTA will stand shoulder to shoulder with the giants on which science buildsupon to benefit future generations.

Artificial Intelligence ; Commerce ; Costs And Cost Analysis ; Disclosure ; Drawing ; Efficiency ; Family Characteristics ; Forecasting ; Goals ; Gymnastics ; Health ; Health Resources ; Industry ; Intelligence ; Inventions ; Language ; Literature ; Methods ; Play And Playthings ; Policy ; Publications ; Publishing ; Research ; Residence Characteristics ; Role ; Science ; Shoulder ; Social Responsibility ; Universities ; Ursidae ; Volition ; Work ; World Health Organization

BACKGROUND AND OBJECTIVE

Randomized controlled trials (RCTs) are essential for advancing evidence-based healthcare by evaluating the effectiveness and safety of health interventions. Despite the increasing recognition of clinical research, the Philippines has had limited contributions to global RCT output. This bibliometric analysis aims to assess the trends, characteristics, and impact of RCTs conducted in the Philippines and published online.

METHODS

A systematic search of Medline (PubMed), and EMBASE, along with Acta Medica Philippina, was conducted to identify published RCTs from January 1990 to October 2022. Eligible studies were screened and analyzed based on publication trends, funding sources, study designs, research settings, and institutional contributions. Descriptive statistics were used to summarize key findings.

RESULTS

A total of 391 RCTs were identified, with a notable increase in number of RCTs published over time. Most studies (91.8%) were published in international journals, and funding was primarily sourced from pharmaceutical companies (47.1%). The predominant RCT design was two-arm parallel (64.7%), with hospitals being the most common research setting (54.2%). Research areas were led by infectious diseases, particularly vaccine-preventable illnesses (23.8%). While the University of the Philippines Manila (21.1%) and the Research Institute for Tropical Medicine (13.7%) were the leading institutions in terms of highest number of published RCTs, foreign authors accounted for nearly half (47.3%) of primary authorships. The most cited studies focused on cardiovascular diseases, infectious diseases, and oncology.

CONCLUSION

The increasing number of published RCTs in the Philippines reflects growth in research capacity and institutional engagement. Strengthening national research dissemination platforms and fostering regional collaborations will be essential in advancing the Philippines’ contribution to global clinical research.

Human ; Bibliometrics ; Bibliometric Analysis ; Philippines ; Publications

OBJECTIVES: To characterize fine particulate matter (PM _2.5)-bound polycyclic aromatic hydrocarbons (PAHs) emitted from different cooking fumes and their exposure routes and assess their health-associated impact to provide a reference for health risk prevention from PAH exposure across different age and sex groups. METHODS: Sixteen PM _2.5-bound PAHs emitted from 11 cooking styles were analyzed using GC-MS/MS. The health hazards of these PAHs in the Handan City population (stratified by age and sex) were predicted using the incremental lifetime cancer risk ( ILCR) model. The respiratory deposition doses ( RDDs) of the PAHs in children and adults were calculated using the PM _2.5 deposition rates in the upper airway, tracheobronchial, and alveolar regions. RESULTS: The total concentrations of PM _2.5-bound PAHs ranged from 61.10 to 403.80 ng/m ³. Regardless of cooking styles, the ILCR _total values for adults (1.23 × 10 ^-6 to 3.70 × 10 ^-6) and older adults (1.28 × 10 ^-6 to 3.88 × 10 ^-6) exceeded the acceptable limit of 1.00 × 10 ^-6. With increasing age, the ILCR _total value first declined and then increased, varying substantially among the population groups. Cancer risk exhibited particularly high sensitivity to short exposure to barbecue-derived PAHs under equivalent body weights. Furthermore, barbecue, Sichuan and Hunan cuisine, Chinese cuisine, and Chinese fast food were associated with higher RDDs for both adults and children. CONCLUSION ILCR _total values exceeded the acceptable limit for both females and males of adults, with all cooking styles showing a potentially high cancer risk. Our findings serve as an important reference for refining regulatory strategies related to catering emissions and mitigating health risks associated with cooking styles.
Humans ; Polycyclic Aromatic Hydrocarbons/analysis* ; Cooking/methods* ; Male ; Female ; Particulate Matter/analysis* ; Adult ; Child ; Middle Aged ; Air Pollutants/analysis* ; Adolescent ; Air Pollution, Indoor/analysis* ; Young Adult ; Child, Preschool ; Aged ; China ; Inhalation Exposure ; Age Factors ; Sex Factors ; Cities ; Infant

OBJECTIVE: Pneumoconiosis, a lung disease caused by irreversible fibrosis, represents a significant public health burden. This study investigates the causal relationships between gut microbiota, gene methylation, gene expression, protein levels, and pneumoconiosis using a multi-omics approach and Mendelian randomization (MR). METHODS: We analyzed gut microbiota data from MiBioGen and Esteban et al. to assess their potential causal effects on pneumoconiosis subtypes (asbestosis, silicosis, and inorganic pneumoconiosis) using conventional and summary-data-based MR (SMR). Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen, along with protein level data from deCODE and UK Biobank Pharma Proteomics Project, were examined in relation to pneumoconiosis data from FinnGen. To validate our findings, we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping, drug prediction, molecular docking, and Phenome-Wide Association Studies to explore relevant phenotypes of key genes. RESULTS: Three core gut microorganisms were identified: Romboutsia ( OR = 0.249) as a protective factor against silicosis, Pasteurellaceae ( OR = 3.207) and Haemophilus parainfluenzae ( OR = 2.343) as risk factors for inorganic pneumoconiosis. Additionally, mapping and quantitative trait loci analyses revealed that the genes VIM, STX8, and MIF were significantly associated with pneumoconiosis risk. CONCLUSIONS This multi-omics study highlights the associations between gut microbiota and key genes ( VIM, STX8, MIF) with pneumoconiosis, offering insights into potential therapeutic targets and personalized treatment strategies.
Humans ; Male ; East Asian People/genetics* ; Europe ; Gastrointestinal Microbiome ; Lung ; Macrophage Migration-Inhibitory Factors/metabolism* ; Mendelian Randomization Analysis ; Multiomics ; Pneumoconiosis/microbiology* ; Intramolecular Oxidoreductases

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

OBJECTIVE: To investigate the association between long-term exposure to ambient fine particulate matter (PM _2.5) and its constituents and the risk of incident type 2 diabetes mellitus (T2DM), and to examine the modification roles of overweight status. METHODS: This prospective study included 27,507 adults living in rural China. The annual mean residential exposure to PM _2.5 and its constituents was estimated using a satellite-based statistical model. Cox models were used to estimate the risk of T2DM associated with PM _2.5 and its constituents. Stratified analysis quantified the role of overweight status in the association between PM _2.5 constituents and T2DM. RESULTS: Over a median follow-up of 9.4 years, 3,001 new T2DM cases were identified. The hazard ratio ( HR) for a 10 μg/m ³ increase in ambient PM _2.5 was 1.30 (95% confidence interval [ CI]: 1.17, 1.45). Among the constituents, the strongest association was observed with black carbon. Being overweight significantly modified the association between certain constituents and the risk of T2DM. Participants who were overweight and exposed to the highest quartile of PM _2.5 constituents had the highest risk of T2DM ( HR: 2.46, 95% CI: 2.04, 2.97). CONCLUSIONS Our findings indicate that PM _2.5 was associated with an increased risk of T2DM, with black carbon potentially being the primary contributor. Being overweight appeared to enhance the association between PM _2.5 and T2DM. This suggests that controlling both PM _2.5 exposure and overweight status may reduce the burden of T2DM.
Humans ; Diabetes Mellitus, Type 2/chemically induced* ; China/epidemiology* ; Particulate Matter/analysis* ; Overweight/epidemiology* ; Female ; Male ; Middle Aged ; Rural Population ; Air Pollutants/analysis* ; Adult ; Prospective Studies ; Environmental Exposure/adverse effects* ; Aged ; Risk Factors

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions. METHODS: Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations. RESULTS: PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM _2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions. CONCLUSION Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans ; China/epidemiology* ; Pulmonary Disease, Chronic Obstructive/chemically induced* ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Male ; Female ; Middle Aged ; Aged ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Spatio-Temporal Analysis ; Adult ; Sand ; Air Pollution