METHODS: For this systematic review and meta-analysis, we searched PubMed, Embase, Scopus, and the Cochrane Library from inception to May 1, 2019, for relevant original research articles without any language restrictions. The literature search and data extraction were done independently by two investigators. Primary outcomes were the prevalence of non-obese or lean people within the NAFLD group and the prevalence of non-obese or lean NAFLD in the general, non-obese, and lean populations; the incidence of NAFLD among non-obese and lean populations; and long-term outcomes of non-obese people with NAFLD. We also aimed to characterise the demographic, clinical, and histological characteristics of individuals with non-obese NAFLD.
FINDINGS: We identified 93 studies (n=10 576 383) from 24 countries or areas: 84 studies (n=10 530 308) were used for the prevalence analysis, five (n=9121) were used for the incidence analysis, and eight (n=36 954) were used for the outcomes analysis. Within the NAFLD population, 19·2% (95% CI 15·9-23·0) of people were lean and 40·8% (36·6-45·1) were non-obese. The prevalence of non-obese NAFLD in the general population varied from 25% or lower in some countries (eg, Malaysia and Pakistan) to higher than 50% in others (eg, Austria, Mexico, and Sweden). In the general population (comprising individuals with and without NAFLD), 12·1% (95% CI 9·3-15·6) of people had non-obese NAFLD and 5·1% (3·7-7·0) had lean NAFLD. The incidence of NAFLD in the non-obese population (without NAFLD at baseline) was 24·6 (95% CI 13·4-39·2) per 1000 person-years. Among people with non-obese or lean NALFD, 39·0% (95% CI 24·1-56·3) had non-alcoholic steatohepatitis, 29·2% (21·9-37·9) had significant fibrosis (stage ≥2), and 3·2% (1·5-5·7) had cirrhosis. Among the non-obese or lean NAFLD population, the incidence of all-cause mortality was 12·1 (95% CI 0·5-38·8) per 1000 person-years, that for liver-related mortality was 4·1 (1·9-7·1) per 1000 person-years, cardiovascular-related mortality was 4·0 (0·1-14·9) per 1000 person-years, new-onset diabetes was 12·6 (8·0-18·3) per 1000 person-years, new-onset cardiovascular disease was 18·7 (9·2-31·2) per 1000 person-years, and new-onset hypertension was 56·1 (38·5-77·0) per 1000 person-years. Most analyses were characterised by high heterogeneity.
INTERPRETATION: Overall, around 40% of the global NAFLD population was classified as non-obese and almost a fifth was lean. Both non-obese and lean groups had substantial long-term liver and non-liver comorbidities. These findings suggest that obesity should not be the sole criterion for NAFLD screening. Moreover, clinical trials of treatments for NAFLD should include participants across all body-mass index ranges.
FUNDING: None.
METHODS: Data were derived from the Global School-Based Student Health Survey (GSHS). Data from 71176 adolescents aged 12-15 years residing in 23 countries were analyzed. The Centers for Disease Control and Prevention (CDC) 2000 growth charts were used to identify underweight, normal weight, and overweight/ obesity. Weighted age- and gender-adjusted prevalence of weight categories and tobacco use was calculated. Multivariate logistic regression analysis was performed to estimate the association between weight categories and tobacco use for each country, controlling for covariates. Pooled odds ratios and confidence intervals were computed using random- or fixed-effects meta-analyses.
RESULTS: A significant association between weight categories and tobacco use was evident in only a few countries. Adolescents reporting tobacco use in French Polynesia, Suriname, and Indonesia, had 72% (95% CI: 0.15-0.56), 55% (95% CI: 0.24-0.84), and 24% (95% CI: 0.61-0.94) lower odds of being underweight, respectively. Adolescents reporting tobacco use in Uganda, Algeria, and Namibia, had 2.30 (95% CI: 1.04-5.09), 1.71 (95% CI: 1.25-2.34), and 1.45 (95% CI: 1.00-2.12) times greater odds of being overweight/obese, but those in Indonesia and Malaysia had 33% (95% CI: 0.50-0.91) and 16% (95% CI: 0.73-0.98) lower odds of being overweight/obese.
CONCLUSIONS: The association between tobacco use and BMI categories is likely to be different among adolescents versus adults. Associating tobacco use with being thin may be more myth than fact and should be emphasized in tobacco prevention programs targeting adolescents.
METHOD: A total of 2247 PET/CT patients with normal glucose level underwent 18F-FDG-whole body imaging procedures. The 18F-FDG dose of 3.7MBq per kg of patient weight administered via intravenous infusion. For CT parameters, kilovoltage of 140keV and current of 40 mAs were used for all studies. All the acquired images collected retrospectively and the effective dose was calculated for each patient using algorithm adapted from ICRP Publication 106, modified for patient weight and patient blood volume. The estimated effective doses were evaluated for patients' body weight and BMI.
RESULTS: The mean of total effective dose and standard deviation is approximately 15.08(4.52) mSv using ICRP algorithm. 56% of total patient has normal BMI and their average total effective dose is 13.6mSv. Underweight patients' effective dose can be as low as 9.6mSv even using diagnostic CT protocols.
CONCLUSION: The effective dose of PET/CT procedure in present study is one of the lowest although using diagnostic parameters for CT acquisition compared to published data worldwide. This is due to the improved sensitivity of PET and complex reconstruction technique that maintains the image quality. A significant association between body weight, BMI and effective dose is reported in present study. Therefore, it is suggested that attention must be given for underweight and ideal BMI patients while prescribing FDG activity and CT imaging parameters in order to minimize the effective dose. The effective dose reported in present study can be considered as an upper limit for effective dose in PET/CT patients with normal BMI. This upper limit can be treated as a standard limit when optimizing imaging parameters, developing algorithm for image reconstruction and prescribing activity for patients. This practice could fulfill ALARA principle that could reduce cancer risk.
METHODS: Two hundred subjects (104 patients, 96 controls) underwent extensive clinical phenotyping. Stool samples were analyzed using 16S rRNA gene sequencing. Fecal metabolomics were performed using two platforms, nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry.
RESULTS: Fecal microbiome and metabolome composition in PD was significantly different from controls, with the largest effect size seen in NMR-based metabolome. Microbiome and NMR-based metabolome compositional differences remained significant after comprehensive confounder analyses. Differentially abundant fecal metabolite features and predicted functional changes in PD versus controls included bioactive molecules with putative neuroprotective effects (eg, short chain fatty acids [SCFAs], ubiquinones, and salicylate) and other compounds increasingly implicated in neurodegeneration (eg, ceramides, sphingosine, and trimethylamine N-oxide). In the PD group, cognitive impairment, low body mass index (BMI), frailty, constipation, and low physical activity were associated with fecal metabolome compositional differences. Notably, low SCFAs in PD were significantly associated with poorer cognition and low BMI. Lower butyrate levels correlated with worse postural instability-gait disorder scores.
INTERPRETATION: Gut microbial function is altered in PD, characterized by differentially abundant metabolic features that provide important biological insights into gut-brain pathophysiology. Their clinical relevance further supports a role for microbial metabolites as potential targets for the development of new biomarkers and therapies in PD. ANN NEUROL 2021;89:546-559.
METHODS: 93 patients and 78 spousal/sibling controls underwent comprehensive assessment of diet, clinical status, muscle strength/performance, frailty, body composition (using dual-energy X-ray absorptiometry), and serum levels of neurogastrointestinal hormones and inflammatory markers.
RESULTS: PD patients were older than controls (66.0 ± 8.5 vs. 62.4 ± 8.4years, P = 0.003). Mean body mass index (24.0 ± 0.4 vs. 25.6 ± 0.5kg/m2, Padjusted = 0.016), fat mass index (7.4 ± 0.3 vs. 9.0 ± 0.3kg/m2, Padjusted<0.001), and whole-body fat percentage (30.7 ± 0.8 vs. 35.7 ± 0.9%, Padjusted<0.001) were lower in patients, even after controlling for age and gender. There were no between-group differences in skeletal muscle mass index and whole-body bone mineral density. Body composition parameters did not correlate with disease duration or motor severity. Reduced whole-body fat percentage was associated with higher risk of motor response complications as well as higher levels of insulin-growth factor-1 and inflammatory markers. PD patients had a higher prevalence of sarcopenia (17.2% vs. 10.3%, Padjusted = 0.340) and frailty (69.4% vs. 24.2%, Padjusted = 0.010). Older age and worse PD motor severity were predictors of frailty in PD.
CONCLUSIONS: We found reduced body fat with relatively preserved skeletal muscle mass, and a high prevalence of frailty, in PD. Further studies are needed to understand the patho-mechanisms underlying these alterations.
DESIGN: Population-based, cross-sectional survey, Nepal Demographic and Health Survey 2011.
SETTING: A nationally representative sample of 11 085 households selected by a two-stage, stratified cluster sampling design to interview eligible men and women.
SUBJECTS: Children (n 2591) aged 0-60 months in a sub-sample of households selected for men's interview.
RESULTS: Prevalence of moderate and severe household food insecurity was 23·2% and 19·0%, respectively, for children aged 0-60 months. Weighted prevalence rates for stunting (height-for-age Z-score (HAZ)