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Study population

This study was a cross-sectional study based on a registered household population aged 65 years or older who underwent a physical examination from January 1, 2021, to December 31, 2021, in Xiamen, Fujian Province, China. Subjects aged ≥ 65 years in the community were informed whether to participate in the physical examination voluntarily. We included 228,664 older adults who completed the survey. Subjects with hepatic steatosis via abdominal ultrasonography (HD-15; Philips, Netherlands); presence of ≥ 1 metabolic risk factor: 1) Body mass index (BMI) ≥ 25 kg/m² or waist circumference (WC) > 94 cm (males) and > 80 cm (females); 2) Fasting blood glucose ≥ 5.6 mmol/L or hemoglobin A1c ≥ 5.7% or a previous diagnosis of diabetes or treatment for diabetes; 3) Blood pressure ≥ 130/85 mmHg or treatment for hypertension; 4) Triglyceride (TG) ≥ 1.7 mmol/L or lipid-lowering therapy; 5) High-density lipoprotein cholesterol (HDL) ≤ 1 mmol/L (males) or ≤ 1.3 mmol/L (females) or lipid-lowering therapy; and without treatment for hepatitis B or without significant alcohol consumption (alcohol consumption of ≥ 30 g ethanol/day in men and ≥ 20 g ethanol/day in women²⁰) were diagnosed as MASLD¹.

To investigate the association between APs and liver fibrosis in MASLD, the following exclusion criteria were applied: (1) subjects without ultrasound examination (n = 94,276); (2) subjects with liver cirrhosis detected by ultrasound (n = 62); (3) subjects without valid APs exposure values due to incomplete address information (n = 46,005); (4) non-MASLD (n = 64,434). Finally, 23,887 MASLD subjects were enrolled.

We performed this study according to the tenets of the Declaration of Helsinki. This work was part of the routine procedure of Health Management Services for the elderly in the national basic public health services in China²¹. Written informed consent was obtained from all participants. The study protocol was approved by the Ethics Committee of Xiamen Center for Disease Control and Prevention [ID: XJK/LLSC (2024) 016]. All the data analyzed was anonymized.

Assessment of covariates

In all subjects, a standardized questionnaire survey was conducted to collect sociodemographic characteristics, lifestyle factors (smoking, alcohol intake, and physical activity), and medication history; medical examinations included height, weight, WC, blood pressure, blood biochemistry, hemoglobin A1c, and abdominal ultrasonography. The indicators of blood biochemistry, including fasting blood glucose, TG, total cholesterol (TC), low-density lipoprotein cholesterol (LDL), HDL, alanine transaminase (ALT), aspartate transaminase (AST), and platelet count of each subject, were evaluated using an auto-analyzer (AU5800; Beckman, California, USA).

Subjects who smoked at least 1 cigarette per day with continuous smoking for more than 6 months were defined as current smokers. Daily alcohol consumption was calculated as the volume of alcohol consumed per day (g) × alcohol concentration (%) × 0.8²². Subjects with alcohol consumption > 0 g ethanol/day were defined as drinkers. The self-reported physical activity frequency was classified as inactive, occasional, often (> 1 time/week), and daily. BMI was calculated as weight divided by the square of height (kg/m²). WC was measured at the midpoint between the lower border of the rib cage and iliac crest, and central obesity was defined as a waist circumference ≥ 90 cm in men and ≥ 85 cm in women²³. Hypertension was defined as systolic blood pressure of ≥ 140 mm Hg and/or diastolic blood pressure of ≥ 90 mm Hg and/or a history of antihypertensive medication and/or a self-reported history of hypertension. Diabetes was defined as a fasting blood glucose concentration ≥ 7.0 mmol/L, and/or a history of antidiabetic medication, and/or a self-reported history of diabetes.

Exposure assessment

The exposure data of O₃, PM_2.5, and PM₁₀ (spatial resolution 1 km × 1 km) were obtained from China high air pollutants (CHAP) dataset. The concentration data of sulfur dioxide (SO₂), carbon monoxide (CO), and NO₂ (spatial resolution 15 km × 15 km) were sourced from a high-resolution air quality reanalysis dataset over China (CAQRA) dataset. Different sources of pollutants, such as traffic, industrial emissions, and domestic heating, were considered in these databases. Participants’ residential addresses were converted into geographic coordinates using the Baidu Map API (https://lbsyun.baidu.com/) and subsequently integrated into the CHAP and CAQRA datasets using the k-nearest neighbor algorithm for spatial analysis. Daily exposure levels of PM_2.5, PM₁₀, O₃, SO₂, CO, and NO₂ were matched to each participant based on their geographic location. The average exposures over 1-year and 2-year periods were computed, with these periods being defined as exactly 1-year and 2-year preceding the date of the medical examinations, respectively. Two-year average levels of AP were considered as the exposure variable in the main analyses.

Diagnosis of liver fibrosis

Liver fibrosis in patients with MASLD was evaluated by metabolic dysfunction-associated fibrosis 5 (MAF-5)²⁴ and Fibrosis-4 index (FIB-4)²⁵. The MAF-5 score is a newly validated, age-independent referral tool to identify individuals at high risk of liver fibrosis with a relevant improvement of fibrosis case-finding in older populations. MAF-5 was calculated as follows: -11.3674 + WC (cm) × 0.0282 – BMI (kg/m²) × 0.1761 + WC (cm) × BMI (kg/m²) × 0.0019 + 2.0762 for diabetes (yes = 1, no = 0) + ln [AST (U/L)] × 2.9207 – platelet count (10⁹/L) × 0.0059. A MAF-5 score of < 0, 0–1, and ≥ 1 was considered a strong predictor of low, medium, and high liver fibrosis risk, respectively. FIB-4 was calculated as follows: age (years) × AST (U/L)/ [platelet count (10⁹/L) × ALT (U/L)^1/2]. A low FIB-4 score of < 2 was considered a strong predictor of the absence of liver fibrosis in the elderly.

Statistical analyses

We described and compared the characteristics of MASLD subjects with low to medium liver fibrosis risk (MAF-5 < 1) and high liver fibrosis risk (MAF-5 ≥ 1). If following normal distribution, continuous variables were presented as mean ± standard deviation and compared by t-test. If not, they were presented as medians (interquartile range) and compared by the Mann–Whitney U test. Categorical variables were presented as numbers (%) and compared by the Pearson chi-square test or the Fisher exact probability test. We used restricted cubic splines with three knots to explore the dose–response relationship between APs and liver fibrosis in MASLD. Then, we divided all the participants into quartiles according to AP concentration. Using the lowest quartile group as the reference, we conducted unadjusted-, age-, sex-adjusted, and multivariate-adjusted (further adjusted for BMI, ALT, hypertension, diabetes, central obesity, physical activity, smoking, and alcohol drinking status) logistic regression models to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for liver fibrosis risk in the higher quartile groups.

To better understand the overall effect of the mixture of APs, we assessed the combined effect of the AP mixture on liver fibrosis using a quantile g-computation model based on the R qgcomp package²⁶. This model was used to estimate the change in liver fibrosis risk for a synchronous one-quartile increase for all APs. The plot depicts APs and liver fibrosis prediction at the joint exposure levels via quantile g-computation and bootstrap variance with a bootstrap of up to 1000. The model was adjusted for age, sex, BMI, ALT, hypertension, diabetes, central obesity, physical activity, smoking, and alcohol drinking status.

We conducted a stratified analysis to test the potential interaction between sex, age, BMI, central obesity, diabetes, hypertension, alcohol consumption, smoking status, physical activity, and APs in liver fibrosis development in MASLD. To validate the robustness of the results, five sensitivity analyses were performed: (1) applying two-pollutant models to assess the confounding effects of co-occurring pollutants; (2) using additional noninvasive indices, i.e., FIB-4, as diagnosis criteria of liver fibrosis; (3) using a 1-year average of APs to assess long-term exposure; (4) excluding participants with medium risk of liver fibrosis (MAF-5 of 0–1); (5) calculating E-value to assess the robustness of our findings to unmeasured confounding²⁷. The E-value quantifies the minimum strength of association that an unmeasured confounder would need to have with both the exposure and outcome to explain away the observed association.

All data were analyzed using SAS software, version 9.4 (SAS Institute, Cary, NC), and R software, version 4.4.0, with two-sided tests and P < 0.05 as statistically significant.

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New research lays groundwork for future studies exploring the role of probiotics in antimicrobial stewardship and infection control among preterm babies.

Preterm babies with very low birth weight who received a probiotic alongside antibiotics had fewer multidrug resistant bacteria and a more typical gut microbiome, a new study shows.

The paper published in Nature Communications today (date date) is the result of a trial testing probiotics among a group of 34 pre-term babies born with a very low birth weight, under 1500g representing around 1-1.5% of babies born around the world. The study sequenced gut bacteria from the babies during the first three weeks after birth.

The collaborative study led by Professor Lindsay Hall and Dr Raymond Kiu from the University of Birmingham found that among babies who received a probiotic treatment of a certain strain including Bifidobacterium alongside antibiotics, levels of typical bacterial strains associated with early-life gut microbiota were at levels typical among full-term babies, reducing both the abundance of antibiotic resistance genes and the number of multi-drug resistant bacteria in the gut.

In the context of the global AMR crisis, this is a major finding, especially for NICUs where preterm infants are especially vulnerable. Probiotics are now used in many neonatal ICUs around the UK, and the WHO have recommended probiotic supplementation in preterm babies. Our paper shows how beneficial this intervention can be for babies born prematurely to help them give their gut a kickstart, and reduce the impact of concerning pathogens taking hold.Professor Lindsay Hall – University of Birmingham

There were lower levels of drug-resistant pathogens including Enterococcus associated with risks of infections and longer hospital stays. Babies who received probiotics also saw higher levels of certain positive bacteria found naturally in the gut.

Among babies who didn’t receive probiotics, analysis of the gut bacteria found that while some differences occurred between those receiving antibiotics or not, both groups saw a dominant microbiome develop that included key bacteria (pathobionts) that can cause health problems including life-threatening infections during the crucial period after birth, as well as in later life.

Professor Lindsay Hall from the University of Birmingham and a group leader at Quadram Institute Bioscience, and senior corresponding author of the study said: “We have already shown that probiotics are highly effective in protecting vulnerable preterm babies from serious infections, and this study now reveals that these probiotics also significantly reduce the presence of antibiotic resistance genes and multidrug-resistant bacteria in the infant gut. Crucially, they seem to do so selectively – targeting resistant strains without disrupting non-resistant strains that might be beneficial.

“In the context of the global AMR crisis, this is a major finding, especially for NICUs where preterm infants are especially vulnerable. Probiotics are now used in many neonatal ICUs around the UK, and the WHO have recommended probiotic supplementation in preterm babies.

“Our paper shows how beneficial this intervention can be for babies born prematurely to help them give their gut a kickstart, and reduce the impact of concerning pathogens taking hold.”

Dr Raymond Kiu from the University of Birmingham, first and co-corresponding author of the paper said: “Sequencing technology has now confirmed that probiotic Bifidobacterium rapidly replicates in the preterm gut during the first three weeks of life. Importantly, this successful colonisation drives the maturation of the gut microbiota and is linked to a noticeable reduction in multi-drug-resistant pathogens—pointing to its pivotal role in improving neonatal health. Our findings also shed light on the complex interactions between antibiotics, probiotics, and horizontal gene transfer (HGT) in shaping the early-life microbiome.

“We believe this research lays the groundwork for future studies exploring the role of probiotics in antimicrobial stewardship and infection control among preterm populations.”