The COVID-19 pandemic has presented multifaceted challenges globally, impacting adolescent health. Among these, food security and nutrition are intertwined closely with mental health outcomes. In Indonesia, with its diverse socio-economic landscape, these interconnections may have been exacerbated by the pandemic. This study investigated the relationship between food security, nutrition and adolescent mental health in Indonesia during COVID-19. Longitudinal data were collected from 511 adolescent boys and girls in 2021–2022 in Gunungkidul district, Yogyakarta. Food security was measured using the Household Food Insecurity Access Scale (HFIAS), and the validated Kessler-10 Psychological Distress Scale (K10) was used to measure adolescent depression. Multivariate linear regression and linear mixed-effects regression were employed to explore associations between these variables, while adjusting for sex, age, pubertal status and household income. Overall, food insecurity score was positively associated with depressive symptoms (β: 0·72, 95 % CI 0·52, 0·92), while BMI z-score was inversely associated (β: −0·31, 95 % CI 0·68, −0·03). We found an increase in strength of association between food insecurity and depressive symptoms over time (moderately food-insecure: β: 1·36 (95 % CI −0·10, 2·83) to 4·63 (95 % CI 2·17, 7·09); severely food-insecure: β: 1·89 (95 % CI 0·36, 3·41) to 3·30 (95 % CI 1·50, 5·10). Enhancing food access, improving nutritional status and providing mental health support are crucial components of adolescent health.

This study aimed to estimate the nationwide prevalence of cardiometabolic diseases (CMD) among adults with underweight in the US general population. Using data from the National Health and Nutrition Examination Survey (1999–2020), we estimated the age-standardised prevalence of dyslipidemia, hypertension, diabetes, chronic kidney disease, CVD and the presence of zero or at least two CMD. Multivariable Poisson regressions were used to compare CMD prevalence between subgroups, adjusting for age, sex and race/ethnicity. Among the 855 adults with underweight included, the weighted mean age was 40·8 years, with 68·1 % being women and 70·4 % non-Hispanic White. The estimated prevalence rates were 23·4 % for dyslipidemia (95 % CI 19·4 %, 27·5 %), 15·6 % for hypertension (95 % CI 13·3 %, 17·8 %), 2·5 % for diabetes (95 % CI 1·5 %, 3·5 %), 7·9 % for chronic kidney disease (95 % CI 6·9 %, 8·8 %) and 6·1 % for CVD (95 % CI 4·3 %, 7·9 %). The prevalence of having zero and at least two CMD was 50·6 % (95 % CI 44·1 %, 57·0 %) and 12·3 % (95 % CI 8·1 %, 16·4 %), respectively. Non-Hispanic Black adults had significantly higher prevalence of diabetes (adjusted prevalence ratio, 3·35; 95 % CI 1·35, 8·30) compared with non-Hispanic White adults. In conclusion, approximately half of the underweight adults had at least one CMD, and 12·3 % had at least two CMD. Prevention and management of CMD in underweight adults are critical yet neglected public health challenges.

Several novel anthropometric indices, including paediatric body adiposity index (BAIp) and triponderal mass index (TMI), have emerged as potential tools for estimating body fat in preschool children. However, their comparative validity and accuracy, particularly when compared with established indicators such as BMI, have not been thoroughly investigated. This cross-sectional study enrolled 2869 preschoolers aged 3–6 years in Wuhan, China. The non-parametric Bland–Altman analysis was employed to evaluate the agreement between BMI, BAIp and TMI with percentage of body fat (PBF), determined by bioelectrical impedance analysis (BIA), serving as the reference measure of adiposity. Additionally, receiver operating characteristic curve analysis was conducted to assess the effectiveness of BMI, BAIp and TMI in screening for obesity. BAIp demonstrated the least bias in estimating PBF, showing discrepancies of 3·64 % (95 % CI 3·40 %, 4·12 %) in boys and 3·95 % (95 % CI 3·79 %, 4·23 %) in girls. Conversely, BMI underestimated PBF by 3·89 % (95 % CI 3·70 %, 4·37 %) in boys and 4·81 % (95 % CI 4·59 %, 5·09 %) in girls, while TMI also underestimated PBF by 5·15 % (95 % CI 4·90 %, 5·52 %) in boys and 5·68 % (95 % CI 5·30 %, 5·91 %) in girls. BAIp exhibited the highest AUC values (AUC = 0·867–0·996) in boys, whereas in girls, there was no statistically significant difference between BMI (AUC = 0·936, 95 % CI 0·921, 0·948) and BAIp (AUC = 0·901, 95 % CI 0·883, 0·916) in girls (P = 0·054). In summary, when considering the identification of obesity, BAIp shows promise as a screening tool for both boys and girls.

The associations between obesity and liver diseases are complex and diverse. To explore the causal relationships between obesity and liver diseases, we applied two-sample Mendelian randomisation (MR) and multivariable MR analysis. The data of exposures (BMI and WHRadjBMI) and outcomes (liver diseases and liver function biomarker) were obtained from the open genome-wide association study database. A two-sample MR study revealed that the genetically predicted BMI and WHRadjBMI were associated with non-alcoholic fatty liver disease, liver fibrosis and autoimmune hepatitis. Obesity was not associated with primary biliary cholangitis, liver failure, liver cell carcinoma, viral hepatitis and secondary malignant neoplasm of liver. A higher WHRadjBMI was associated with higher levels of biomarkers of lipid accumulation and metabolic disorders. These findings indicated independent causal roles of obesity in non-alcoholic fatty liver disease, liver fibrosis and impaired liver metabolic function rather than in viral or autoimmune liver disease.

Depression is a common prenatal psychological complication. We aimed to investigate if maternal pre-pregnancy diet can impact prenatal depressive symptoms and the mediating role of pre-pregnancy BMI and inflammation. We used data (N 1141) from the Alberta Pregnancy Outcomes and Nutrition cohort study. We calculated Mediterranean diet adherence (MED) and dietary inflammatory index (DII) scores using data from pre-pregnancy FFQ. In the third-trimester, we assessed depressive symptoms using Edinburgh Postpartum Depression Scale (EPDS) and inflammation through serum C-reactive protein (CRP) levels. BMI was calculated from self-reported pre-pregnancy weight. Race-stratified analyses (white and people of colour) were run. We observed no association between MED or DII tertiles and depressive symptoms. However, white participants in the MED tertile-3 had lower risk of depression (EPDS < 10) compared with tertile-1 (OR = 0·56, 95 % CI, 0·33, 0·95). White individuals in MED tertile-3 had lower BMI (MD = –1·08; 95 % CI, −1·77, −0·39) and CRP (MD = –0·53; 95 % CI, −0·95, −0·11) than tertile-1, and those in DII tertile-2 (MD = 0·44; 95 % CI, 0·03, 0·84) and tertile-3 (MD = 0·42; 95 % CI, 0·01, 0·83) had higher CRP than tertile-1. Among people of colour, neither MED nor DII was associated with BMI or CRP, but BMI was negatively associated with depressive symptoms (β = –0·25, 95 % CI, −0·43, −0·06). We found no association between diet and depressive symptoms through BMI or CRP, in either race. Pre-pregnancy diet might affect the risk of prenatal depression in a race-specific way. Further research is required to explore the racial differences in the association between maternal diet and prenatal depressive symptoms/depression risk.

There is significant evidence that an unhealthy diet greatly increases the risk of complications during pregnancy and predisposes offspring to metabolic dysfunction and obesity. While fat intake is typically associated with the onset of obesity and its comorbidities, there is increasing evidence linking sugar, particularly high fructose corn syrup, to the global rise in obesity rates. Furthermore, the detrimental effects of added sugar intake during pregnancy on mother and child have been clearly outlined. Guidelines advising pregnant women to avoid food and beverages with high fat and sugar have led to an increase in consumption of ‘diet’ or ‘light’ options. Examination of some human birth cohort studies shows that heavy consumption (at least one beverage a day) of non-nutritive sweetener (NNS) containing beverages has been associated with increased risk of preterm birth and increased weight/BMI in male offspring independent of maternal weight, which appears to be offset by breastfeeding for 6 months. Rodent models have shown that NNS exposure during pregnancy can impact maternal metabolic health, adipose tissue function, gut microbiome profiles and taste preference. However, the mechanisms underlying these effects are multifaceted and further research, particularly in a translational setting is required to fully understand the effects of NNS on maternal and infant health during pregnancy. Therefore, this review examines maternal sweetener intakes and their influence on fertility, maternal health outcomes and offspring outcomes in human cohort studies and rodent models.

Obesity is an established risk factor for hypertension, but the mechanisms are only partially understood. We examined whether body mass index (BMI)-related DNA methylation (DNAm) variation would mediate the association of BMI with blood pressure (BP). We first conducted a genomewide DNA methylation analysis in monozygotic twin pairs to detect BMI-related DNAm variation and then evaluated the mediating effect of DNAm on the relationship between BMI and BP levels using the causal inference test (CIT) method and mediation analysis. Ontology enrichment analysis was performed for CpGs using the GREAT tool. A total of 60 twin pairs for BMI and systolic blood pressure (SBP) and 58 twin pairs for BMI and diastolic blood pressure (DBP) were included. BMI was positively associated with SBP (β = 1.86, p = .0004). The association between BMI and DNAm of 85 CpGs reached p < 1×10–4 level. Eleven BMI-related differentially methylated regions (DMRs) within LNCPRESS1, OGDHL, RNU1-44P, NPHS1, ECEL1P2, LLGL2, RNY4P15, MOGAT3, PHACTR3, and BAI2 were found. Of the 85 CpGs, 9 mapped to C10orf71-AS1, NDUFB5P1, KRT80, BAI2, ABCA2, PEX11G and FGF4 were significantly associated with SBP levels. Of the 9 CpGs, 2 within ABCA2 negatively mediated the association between BMI and SBP, with a mediating effect of −0.24 (95% CI [−0.65, −0.01]). BMI was also positively associated with DBP (β = 0.60, p = .0495). The association between BMI and DNAm of 193 CpGs reached p < 1×10−4 level. Twenty-five BMI-related DMRs within OGDHL, POU4F2, ECEL1P2, TTC6, SMPD4, EP400, TUBA1C and AGAP2 were found. Of the 193 CpGs, 33 mapped to ABCA2, ADORA2B, CTNNBIP1, KDM4B, NAA60, RSPH6A, SLC25A19 and STIL were significantly associated with DBP levels. Of the 33 CpGs, 12 within ABCA2, SLC25A19, KDM4B, PTPRN2, DNASE1, TFCP2L1, LMNB2 and C10orf71-AS1 negatively mediated the association between BMI and DBP, with a total mediation effect of −0.66 (95% CI [−1.07, −0.30]). Interestingly, BMI might also negatively mediate the association between the DNAm of most CpG mediators mentioned above and BP. The mediating effect of DNAm was also found when stratified by sex. In conclusion, DNAm variation may partially negatively mediate the association of BMI with BP. Our findings may provide new clues to further elucidate the pathogenesis of obesity to hypertension and identify new diagnostic biomarkers and therapeutic targets for hypertension.

This study verified the diagnostic accuracy of the nutritional status classified by the international height and BMI references of the World Health Organization (WHO) (WHO/2007), International Obesity Task Force (IOTF/2012) and MULT (2023). The data pool was composed by 22 737 subjects aged five to 16 years from the Santos and Porto Alegre surveys. A correlation matrix between the z-scores of the BMI references and the skinfold measurements was calculated through the Pearson correlation coefficient (r), and the subject’s nutritional status was classified according to the international growth references. The accuracy for diagnosing obesity was performed separately by sex and using the 95th percentile of the triceps and subscapular skinfold sum, while Lin’s concordance coefficient, Bland–Altman method and the Cohen’s Kappa coefficient (Kappa) were used to verify the concordance and reliability among the BMI references. The correlation matrix showed a high positive correlation among the BMI z-scores (r ≥ 0·99) and among the skinfold measurements (r ≥ 0·86). The prevalence of stunting was higher when applying the MULT reference (3·4 %) compared with the WHO reference (2·3 %). The Bland–Altman plots showed the lowest critical difference (CD) between the height references of WHO and MULT (CD = 0·22). Among the BMI references, the WHO obesity percentile presented lower performance than MULT for boys, presenting a lower +LR value (WHO = 6·99/MULT 18 years = 10·99; 19 years = 8·99; 20 years = 8·09) for the same −LR values (0·04). Therefore, MULT reference holds promise as a valuable tool for diagnosing childhood obesity, particularly when considering sex differences. This enhances its suitability for assessing the nutritional status of Brazilian schoolchildren.

Excess body weight is associated with increased mortality and risk of developing CVD. Body fat distribution is now considered a better indicator of disease risk than BMI, with central adiposity associated with dyslipidaemia and insulin resistance. Dietary modification is unquestionably important in the prevention of obesity and CVD, with the type but not the amount of dietary fat emerging as an important determinant of both diseases. Although reducing SFA intake via replacement with unsaturated fatty acids (UFA) is a key public health strategy for CVD prevention, variability in the lipid lowering response has been observed. This narrative review aims to investigate the link between adiposity and CVD risk, and the role of dietary fat composition and APOLIPOPROTEIN (APO)E genotype on this relationship. In the absence of weight loss, replacing dietary SFA with UFA reduces central adiposity and anthropometric measures, and is linked with lower total and LDL-cholesterol concentrations. However, differences in study populations and body composition techniques need to be taken into consideration. To date, only a limited number of studies have determined the role of APOE on body composition and CVD risk, but findings are inconsistent. Both APOE2 and APOE4 alleles have been correlated with adiposity related markers, and an APOE genotype–BMI interaction has been reported on fasting lipids. However, studies are often performed retrospectively leading to small sample sizes within the genotype groups. Further studies are needed to confirm the relationship between APOE genotype, adiposity and circulating CVD risk markers.

Evidence suggests that differences in meal timing between weekends and weekdays can disrupt the body’s circadian rhythm, leading to a higher BMI. We aimed to investigate the associations between mealtime variation from weekdays to weekends (eating midpoint jetlag), dietary intake and anthropometric parameters, based on individuals’ chronotype. The study utilised data from National Health and Nutrition Examination Survey 2017–2018. Food consumption was estimated by weighted average of participants’ food intake on weekdays and weekends. Eating midpoint jetlag, defined as the difference between the midpoint of the first and last mealtimes on weekends and weekdays, was calculated. Chronotype was assessed by participants’ mid-sleep time on weekends, adjusted for sleep debt. Linear regression analysis was conducted to investigate the associations between variables. The sample was categorised into chronotype tertiles. Among individuals in the third chronotype tertile, there was a positive association between eating midpoint jetlag and BMI (β = 1·2; 95 % CI (1·13, 1·27)). Individuals in the first tertile showed a positive association between eating midpoint jetlag and energy (β = 96·9; 95 % CI (92·9, 101·7)), carbohydrate (β = 11·96; 95 % CI (11·2, 12·6)), fat (β = 3·69; 95 % CI (3·4, 3·8)), cholesterol (β = 32·75; 95 % CI (30·9, 34·6)) and sugar (β = 8·84; 95 % CI (8·3, 9·3)) intake on weekends. Among individuals with an evening tendency, delaying meals on weekends appears to be linked to a higher BMI. Conversely, among individuals with a morning tendency, eating meals later on weekends is associated with higher energetic intake on weekends.