Carotenoids are generally associated with health-beneficial effects; however, their intake patterns related to the metabolic syndrome (MetS) and its components remain controversial. This cross-sectional study investigated associations between dietary intakes of individual carotenoids, fruits and vegetables, and the MetS and its components. Dietary intakes of 1346 participants of the Observation des Risques et de la Santé Cardio-Vasculaire au Luxembourg (ORISCAV-LUX-2) study were investigated by a 174-item FFQ, and carotenoid intake was determined by linking findings using mainly the USDA food databases. Components of MetS and complementary variables, including anthropometric (BMI, waist circumferences and waist:hip ratio) and biological parameters (TAG, HDL-cholesterol, fasting blood glucose and blood pressure), were measured. Logistic (for MetS) and linear multivariable regression models (including assessing MetS as scores) adjusted for various confounders were created. α-and β-Carotene, as well as lutein + zeaxanthin, were inversely associated with MetS (also when it was measured on a continuous scale), reducing the odds for MetS by up to 48 %. However, lycopene, phytoene and phytofluene were rather positively associated with MetS scores and its components, though these adverse effects disappeared, at least for lycopene, when controlling for intakes of tomato-based convenience foods, in line with indicating a rather unhealthy/westernised diet. All these associations remained significant when including fruits and vegetables as confounders, suggesting that carotenoids were related to MetS independently from effects within fruits and vegetables. Thus, a high intake of carotenoids was bidirectionally associated with MetS, its severity, risk and its components, depending on the type of carotenoid. Future investigations are warranted to explore the inverse role that tomato-based carotenoids appear to suggest in relation to the MetS.

Automated visual anthropometrics produced by mobile applications are accessible and cost effective with the potential to assess clinically relevant anthropometrics without a trained technician present. Thus, the aim of this study was to evaluate the precision and agreement of smartphone-based automated anthropometrics against reference tape measurements. Waist and hip circumference (WC; HC), waist:hip ratio (WHR) and waist:height ratio (W:HT) were collected from 115 participants (69 F) using a tape measure and two smartphone applications (MeThreeSixty®, myBVI®) across multiple smartphone types. Precision metrics were used to assess test-retest precision of the automated measures. Agreement between the circumferences produced by each mobile application and the reference were assessed using equivalence testing and other validity metrics. All mobile applications across smartphone types produced reliable estimates for each variable with intraclass correlation coefficients ≥ 0·93 (all P < 0·001) and root mean square coefficient of variation between 0·5 and 2·5 %. Precision error for WC and HC was between 0·5 and 1·9 cm. WC, HC, and W:HT estimates produced by each mobile application demonstrated equivalence with the reference tape measurements using 5 % equivalence regions. Mean differences via paired t-tests were significant for all variables across each mobile application (all P < 0·050) showing slight underestimation for WC and slight overestimation for HC which resulted in a lack of equivalence for WHR compared with the reference tape measure. Overall, the results of our study support the use of WC and HC estimates produced from automated mobile applications, but also demonstrates the importance of accurate automation for WC and HC estimates given their influence on other anthropometric assessments and clinical health markers.

Obesity is currently considered a public health problem with pandemic proportions and is associated with chronic low-grade inflammation, which can predispose to the development of several chronic diseases and metabolic complications. This cross-sectional population-based study, conducted with 743 Brazilian adults, aimed to evaluate the association between inflammatory cytokines with anthropometric measurements. Socio-demographic, anthropometric, behavioural and biochemical variables were collected. Multiple linear regression stratified by sex and adjusted for confounding factors was performed. In men, waist circumference (WC) was associated with IL-1β (3·52 pg/ml; 95 % CI 0·60, 6·45), IL-6 (6·35 pg/ml; 95 % CI 0·35, 12·34), IL-8 (8·77 pg/ml; 95 % CI 2·37, 15·17), IL-10 (3·09 pg/ml; 95 % CI 0·56, 5·61), IL12p70 (8·31 pg/ml; 95 % CI 3·11, 13·52) and TNF-α (4·22 pg/ml; 95 % CI 0·20, 10·48). Waist:height ratio was associated with IL-6 (3·21 pg/ml; 95 % CI 0·02, 6·39). BMI was associated with IL-1β (1·50 pg/ml; 95 % CI 0·46, 2·34), IL-6 (2·97 pg/ml; 95 % CI 0·78, 5·16), IL-8 (4·48 pg/ml; 95 % CI 2·21, 6·75), IL-10 (1·31 pg/ml; 95 % CI 0·30, 2·31), IL-12p70 (3·59 pg/ml; 95 % CI 1·24, 5·95) and TNF-α (2·00 pg/ml; 95 % CI 0·81, 3·19). In women, WC was associated with IL-6 (5·10 pg/ml; 95 % CI 0·68, 9·51) and IL-10 (4·16 pg/ml; 95 % CI 1·26, 7·06). BMI was associated with IL-6 (2·67 pg/ml; 95 % CI 0·34, 4·99), and WHR was associated with TNF-α (2·84 pg/ml; 95 % IC 0·86–6·54). The results highlight the importance of anthropometric assessment in clinical practice and the need to develop public policies and interventions to reduce the prevalence of obesity and, consequently, of inflammation and possible metabolic complications.

We aimed to investigate the anthropometric and body composition parameters associated with the metabolically obese normal-weight (MONW) phenotype. This cross-sectional study was conducted with 506 adolescents in Brazil (aged 10–19 y). The MONW phenotype was defined as normal-weight, according to BMI/age, and at least one metabolic alteration. Anthropometric measurements were obtained and the DEXA was used for body composition analysis. Crude and adjusted Poisson regression models with robust variance were used to estimate the associations. The phenotype was positively associated with waist circumference (male: prevalence ratio (PR) = 1·05; 95% CI 1·01, 1·09; female: PR = 1·06; 95% CI 1·02, 1·09), waist:height ratio (male: PR = 1·26; 95% CI 1·07, 1·49; female: PR = 1·29; 95% CI 1·07, 1·56) and android:gynoid fat ratio (male: PR = 1·25; 95% CI 1·03, 1·51; female: PR = 1·39; 95% CI 1·20, 1·62), in both sexes. Furthermore, there was a positive association of phenotype with waist:hip ratio (PR = 1·32; 95% CI 1·06, 1·65) and trunk:arm fat ratio (PR = 1·13; 95% CI 1·02, 1·24) only in males and with trunk:leg fat ratio (PR = 2·84; 95% CI 1·46, 5·53), BAIp (PR = 1·06; 95% CI 1·01, 1·12), fat mass index (PR = 1·24; 95% CI 1·10, 1·41) and regional indices of metabolic load and capacity (PR = 1·29; 95% CI 1·09, 1·53), in females. Anthropometric and body composition parameters indicative of central and total fat are associated with the MONW phenotype.

Overweight is increasing in the adolescent population and became a public health problem in the world. This study aimed to identify the body adiposity indices (BAI) with the best capacity to predict excess fat tissue and propose cut-off points for them, according to sex and adolescence period. This is a cross-sectional study. We calculated BMI, conicity index (CI), BAI, body roundness index (BRI), waist:height ratio (WtHR) and waist:hip ratio. Predictive capacity and cut-off points of adiposity indices were established by ROC (receiver operating characteristic) curves. We determined AUC-ROC and CI, stratified by sex and adolescence period. The best index to identify excess body fat in 10-13-year-old female adolescents was the WtHR (AUC = 0·92), like the BAI in girls aged from 14 to 16 years old (AUC = 0·87) and 17 to 19 years old (AUC = 0·80). In male adolescents aged from 10 to 13 years old and 14 to 16 years old, the best index was the WtHR (AUC = 0·93 and AUC = 0·8, respectively), like the BAI in boys aged from 17 to 19 years old (AUC = 0·95). The use of indices with specific cut-off points for each period of adolescence and according to sex is important for the reliable diagnosis of excess body fat. It is advisable to use indices together to obtain a more accurate assessment. Thus, the WtHR and BAI are reproducible and reliable, with high sensitivity and specificity values, and can be used together with the BMI.

This meta-analysis aimed to study the relationship between abdominal obesity and the risk of CVD by waist circumference (WC), waist:hip ratio (WHR) and waist:height ratio (WHtR). We systematically searched PubMed, Embase and Web of Science. Prospective studies that estimated cardiovascular events by WC, WHR and WHtR were included in this study. Pooled relative risks with 95 % CI were calculated using random effects models. A total of thirty-one studies were included in the meta-analysis, including 669 560 participants and 25 214 cases. Compared the highest with the lowest category of WC, WHR and WHtR, the summary risk ratios were 1·43 (95 % CI, 1·30, 1·56, P < 0·001), 1·43 (95 % CI, 1·33, 1·54, P < 0·001) and 1·57 (95 % CI, 1·37, 1·79, P < 0·001), respectively. The linear dose–response analysis revealed that the risk of CVD increased by 3·4 % for each 10 cm increase of WC, and by 3·5 and 6·0 % for each 0·1 unit increase of WHR and WHtR in women, respectively. In men, the risk of CVD increased by 4·0 % for each 10 cm increase of WC, and by 4·0 and 8·6 % for each 0·1 unit increase of WHR and WHtR, respectively. Collectively, abdominal obesity is associated with an increased risk of CVD. WC, WHR and WHtR are good indicators for the prediction of CVD.

South Asians, who are at a disproportionately greater risk of atherosclerotic CVD (ASCVD), represent a rapidly growing population in the USA. The relationship between dairy products, a major component of South Asian diets, and body composition – an established risk factor for ASCVD, is unclear. The aim of the present study was to examine associations between dairy intake and multiple measures of body composition (BMI, waist and hip circumference, waist:hip ratio, abdominal lean mass, subcutaneous, visceral, and intermuscular fat areas) among South Asian adults in the USA. A baseline analysis was conducted using existing data from the Mediators of Atherosclerosis in South Asians Living in America cohort. In women, the highest (>1·9 servings/d) v. lowest (<1 serving/d) tertile of dairy intake was associated with 53 % lower odds of a waist circumference >80 cm (95 % CI 0·25, 0·89, Pfor trend<0·05). No associations were observed between dairy intake and measures of body composition. However, >3 servings of low-fat yogurt/week was associated with a 9·9 cm2 lower visceral fat area (95 % CI –19·07, –0·72, P<0·05) and 2·3 cm2 lower intermuscular fat area (95 % CI –3·76, –0·79, P<0·05) as compared with those with three servings/week. Milk and cheese were not associated with body composition measures. These analyses suggest that higher consumption of low-fat yogurt is associated with lower visceral and intermuscular fat in the whole sample, and women with higher dairy intake have lower waist circumference. Our study supports dietary incorporation of dairy products, and recognises the utility of multidimensional measures of central adiposity.

The present study aimed to investigate an interaction between energy intake, physical activity and UCP2 gene variation on weight gain and adiposity changes in Indonesian adults. This is a prospective cohort study conducted in 323 healthy adults living in the city of Yogyakarta, Indonesia. Energy intake, physical activity, body weight, BMI, percentage body fat and waist:hip ratio (WHR) were measured at baseline and after 2 years while UCP2 -866G/A gene variation was determined at baseline. We reported that after 2 years subjects had a significant increment in body weight, BMI, body fat and reduction in WHR (all P < 0·05). In all subjects, total energy intake was significantly correlated with changes in body weight (β = 0·128, P = 0·023) and body fat (β = 0·123, P = 0·030). Among subjects with the GG genotype, changes in energy intake were positively correlated with changes in body weight (β = 0·232, P = 0·016) and body fat (β = 0·201, P = 0·034). These correlations were insignificant among those with AA + GA genotypes (all P > 0·05). In summary, we show that UCP2 gene variation might influence the adiposity response towards changes in energy intake. Subjects with the GG genotype of UCP2 -866G/A gene were more responsive to energy intake, thus more prone to weight gain due to overeating.

Obesity caused by excessive deposited fat is generally classified as BMI ≥ 30 kg/m2. Research regarding the association between dietary advanced glycation end products (dAGE) and obesity is limited. The aim of the present study was to investigate the association between dAGE and obesity and body composition in Iranian adults. This cross-sectional study included 265 adults aged 18–75 years from Tehran, Iran. dAGE were estimated using a validated semi-quantitative FFQ, according to the published food carboxymethyl lysine–AGE database for 549 routinely consumed food items for the Northeastern American multiethnic urban population, and were reported by dividing total energy intake. Dietary intake, sociodemographic data and physical activity status were collected using validated questionnaires, and anthropometric characteristics were measured. Body composition was assessed by bioelectrical impedance analysis, and obesity was defined based on WHO guidelines. The intake of fat and meat was significantly increased in higher tertiles, compared with the first tertile of dAGE (P < 0·001). No association between dAGE and body composition measures and obesity was observed; however, there was a significant negative association between dAGE and BMI (BMI; P = 0·01), waist circumference (P = 0·01), waist:hip ratio (P = 0·03), fat-free mass (P = 0·02) and muscle mass index (P = 0·01) in non-linear models. In conclusion, higher consumption of dAGE was associated with increased intake of fat and meat and was negatively related to changes in body composition measurements. Therefore, dAGE may connect obesity to diet by energy imbalance.

This systematic review and meta-analysis compared the effects of different rates of weight loss (WL), but equivalent total WL, on body composition and RMR. Studies examining gradual v. rapid WL on body composition and RMR in participants with overweight/obesity published up to October 2019 were identified through PubMed, the Cochrane Library, Web of Science, Embase, Scopus and Ovid databases. Meta-analysis was carried out using a fixed or random effects model as appropriate. Although the magnitude of WL was similar (mean difference 0·03 kg, 95 % CI –0·65, 0·71), gradual WL promoted greater reductions in fat mass (FM) (–1 kg, 95 % CI –1·70, –0·29) and body fat percentage (BFP) (–0·83 %, 95 % CI –1·49, –0·17). Gradual WL significantly preserved RMR compared with rapid WL (407·48 kJ, 95 % CI 76·76, 118·01). However, there was no significant difference in waist and hip circumferences, waist:hip ratio and fat-free mass (FFM) between gradual and rapid WL. The present systematic review and meta-analysis indicates beneficial effects of gradual WL, as compared with rapid WL, on FM, BFP and RMR in individuals with overweight/obesity. However, FFM changes and anthropometric indices did not significantly differ following different rates of WL.

Obesity indicators are known to predict the presence of type 2 diabetes mellitus (T2DM); however, evidence for which indicator best identifies undiagnosed T2DM in the Indian population is still very limited. In the present study we examined the utility of different obesity indicators to identify the presence of undiagnosed T2DM and determined their appropriate cut point for each obesity measure. Individuals were recruited from the large-scale population-based Kerala Diabetes Prevention Program. Oral glucose tolerance tests was performed to diagnose T2DM. Receiver operating characteristic (ROC) curve analyses were used to compare the association of different obesity indicators with T2DM and to determine the optimal cut points for identifying T2DM. A total of 357 new cases of T2DM and 1352 individuals without diabetes were identified. The mean age of the study participants was 46⋅4 (sd 7⋅4) years and 62 % were men. Waist circumference (WC), waist:hip ratio (WHR), waist:height ratio (WHtR), BMI, body fat percentage and fat per square of height were found to be significantly higher (P < 0⋅001) among those with diabetes compared with individuals without diabetes. In addition, ROC for WHR (0⋅67; 95 % 0⋅59, 0⋅75), WHtR (0⋅66; 95 % 0⋅57, 0⋅75) and WC (0⋅64; 95 % 0⋅55, 0⋅73) were shown to better identify patients with T2DM. The proposed cut points with an optimal sensitivity and specificity for WHR, WHtR and WC were 0⋅96, 0⋅56 and 86 cm for men and 0⋅88, 0⋅54 and 83 cm for women, respectively. The present study has shown that WHR, WHtR and WC are better than other anthropometric measures for detecting T2DM in the Indian population. Their utility in clinical practice may better stratify at-risk patients in this population than BMI, which is widely used at present.

This study aimed to assess the relationship between the Dietary Inflammatory Index (DII®), a validated tool for evaluating diet-associated inflammation, and anthropometric indices in children and adolescents. This multicentre survey was conducted on 5427 school students selected via multistage cluster sampling from thirty provinces of Iran. This survey was conducted under the framework of the weight disorders survey, which is part of a national surveillance programme entitled Childhood and Adolescence Surveillance and Prevention of Adult Non-communicable Diseases-IV. For calculating the DII scores, twenty-five dietary factors were obtained from a validated 168-item FFQ. Height, weight, wrist circumference, neck circumference (NC), waist circumference (WC) and hip circumference (HC) were measured. BMI z-score, waist circumference:hip circumference ratio (WHR), waist circumference:height ratio (WHtR) and parental BMI were computed. Linear regression models were used to evaluate the association of DII and anthropometric indices. Significant trends were observed across quartiles of DII score for all anthropometric indices in all participants (P <0·05), except for WHR and WHtR. After adjustment for potential confounders, the multiple linear regression analysis for each anthropometric index revealed that participants in the highest DII quartile had higher BMI z-score, WC, HC and parental BMI compared with those in the first (or lowest) quartile. In summary, we found that a pro-inflammatory diet was associated with higher BMI z-score, wrist circumference, NC, WC, HC and parental BMI. The large sample size of the present study may influence the statistical significance of observed associations. Hence, the findings should be clinically interpreted with caution.

Associations between ferritin and insulin sensitivity have been described in recent studies. The possible association showed conflicting results by sex and menopausal status. We aimed to investigate the cross-sectional association of ferritin levels with insulin resistance and β-cell function. A total of 2518 participants (1033 men, 235 pre-menopausal women and 1250 post-menopausal women) were enrolled from the Changfeng Study. A standard interview was conducted, as well as anthropometric measurements and laboratory analyses, for each participant. The serum ferritin level was measured using electrochemiluminescence immunoassay. Insulin resistance and β-cell function indices were derived from a homeostasis model assessment. The results showed that the serum ferritin levels were 250·4 (sd 165·2), 94·6 (sd 82·0) and 179·8 (sd 126·6) ng/ml in the men, pre-menopausal and post-menopausal women, respectively. In fully adjusted models (adjusting for age, current smoking, BMI, waist:hip ratio, systolic blood pressure, diastolic blood pressure, TAG, HDL-cholesterol, LDL-cholesterol, log urine albumin:creatinine ratio, leucocytes, alanine aminotransferase, aspartate aminotransferase and γ-glutamyl transpeptidase), serum ferritin concentrations are significantly associated with insulin resistance in men and post-menopausal females, and the null association was observed in pre-menopausal females. Interestingly, an increased β-cell function associated with higher ferritin was observed in post-menopausal participants, but not in male participants. In conclusion, these results suggested that elevated serum ferritin levels were associated with surrogate measures of insulin resistance among the middle-aged and elderly male and post-menopausal women, but not in pre-menopausal women.

Previous reports investigating adiposity and cognitive function in the population allude to a negative association, although the relationship in older adults is unclear. The aim of this study was to investigate the association of adiposity (BMI and waist:hip ratio (WHR)) with cognitive function in community-dwelling older adults (≥60 years). Participants included 5186 adults from the Trinity Ulster Department of Agriculture ageing cohort study. Neuropsychological assessment measures included the Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Multi-variable linear regression models were used to assess the association between adiposity and cognitive function adjusting for insulin resistance, inflammation and cerebrovascular disease. The mean ages were 80·3 (sd 6·7), 71·0 (sd 7·3) and 70·2 (sd 6·3) years on the cognitive, bone and hypertensive cohorts, respectively. In the cognitive cohort, BMI was positively associated with immediate and delay memory, visuospatial/constructional ability, language and MMSE, and negatively with FAB (log-transformed), whereas WHR was negatively associated with attention. In the bone cohort, BMI was not associated with any cognitive domain, whereas WHR was negatively associated with visuospatial/constructional ability, attention and MMSE. In the hypertensive cohort, BMI was not associated with any cognitive domain, whereas WHR was negatively associated with immediate and delayed memory, visuospatial/constructional ability, language and MMSE and positively with FAB (log-transformed). In the cognitive and bone cohorts, the association of WHR and attention disappeared by further controlling for C-reactive protein and HbA1C. In this study of older adults, central adiposity was a stronger predictor of poor cognitive performance than BMI. Older adults could benefit from targeted public health strategies aimed at reducing obesity and obeseogenic risk factors to avoid/prevent/slow cognitive dysfunction.

Recent evidence has raised the possibility of the existence of a sixth taste modality – that is, taste for fat – which is mediated by lingual CD36 and plays a role in obesity. Consequently, the genetic polymorphism of CD36 has been shown to be associated with altered oro-sensory detection of dietary lipids. In the present study, we investigated the relationship between oro-sensory perception of linoleic acid (LA), two CD36 polymorphisms (rs1527483 and rs3212018), obesity parameters and craving habits for dietary lipids in young Czech adults. We also sequenced 5 and 6 exons of CD36 to trace out any new mutation that might be responsible for the difference in taste perception. We observed that craving for dietary lipids was correlated with anthropometric parameters (P<0·05) and LA detection threshold (P=0·033). The participants with the CC genotype of the rs1527483 polymorphism had lower BMI (P=0·011), waist circumference (P=0·005), waist:height ratio (P=0·010) and higher sensitivity for LA (P=0·037) than the participants with the CT and TT genotypes. Interestingly, we did not observe any association between the rs3212018 polymorphism and the studied parameters. Moreover, we did not observe any mutation in exons 5 and 6 of the CD36 gene in these subjects. Finally, we can state that rs1527483, but not rs3212018, is associated with high body weight in young Czech subjects.

Anthropometric reference data for older adults, particularly for the oldest old, are still limited, especially in developing countries. The aim of the present study was to describe sex- and age-specific distributions of anthropometric measurements and body composition in Mexican older adults. The methods included in the present study were assessment of height, weight, BMI, calf circumference (CC), waist circumference (WC) and hip circumference (HC) as well as knee height in a sample of 8883 Mexican adults aged 60 years and above and the estimation of sex- and age-specific differences in these measures. Results of the study (n 7865, 54 % women) showed that men are taller, have higher BMI, and larger WC than women, whereas women presented higher prevalence of obesity and adiposity. Overall prevalence of underweight was 2·3 % in men and 4·0 % in women, with increasing prevalence with advancing age. Significant differences were found by age group for weight, height, WC, HC, CC, BMI and knee height (P<0·001), but no significant differences in waist–hip circumference were observed. Significant differences between men and women were found in height, weight, circumferences, BMI and knee height (P<0·001). These results, which are consistent with studies of older adults in other countries, can be used for comparison with other Mexican samples including populations living in the USA and other countries with similar developmental and socio-economic conditions. This information can also be used as reference in clinical settings as a tool for detection of individuals at risk of either underweight or overweight and obesity.

Dietary pattern analysis is an epidemiological method designed to consider the complexity of food preferences and diet patterns of populations. Few studies from South Asia have used this methodology to describe population food intake. Our objective was to identify dietary patterns and understand their associations with sociodemographic, anthropometric and life-style factors among low-income Pakistani urban adults. Dietary information was collected by a thirty-three-item FFQ and dietary patterns were derived by principal component analyses in 5491 subjects enrolled in the Control of Blood Pressure and Risk Attenuation (COBRA) study. Three dietary patterns were identified: a fat and sweet pattern characterised by fried snacks/foods, desserts, organ meats, bakery products, Pakistani bread and food purchased from outside the home; a fruit and vegetable pattern including fruits, juices, raw and cooked vegetables, lean meat and low-fat milk; and a seafood and yogurt pattern identified by prawns, fish, potatoes and yogurt. The fat and sweet pattern scores were low among older subjects, those with high BMI and waist circumference but high among females and physically active participants. The fruit and vegetable pattern was associated with younger age, high BMI, education and non-tobacco use. The seafood and yogurt pattern was associated with high BMI, increased physical activity and non-tobacco use. In conclusion, distinct dietary patterns exist for the Pakistani population that may be related to some of the population characteristics and thus may have importance in suggesting dietary and life-style interventions in the prevention of chronic diseases.

We examined longitudinal associations of vitamin D receptor (VDR) and megalin (LRP2; LDL receptor-related protein-2) gene polymorphisms with central adiposity. We used data from the Baltimore Longitudinal Study of Aging (BLSA), an ongoing prospective open cohort study. Study participants consisted of non-Hispanic white adults residing in Baltimore city, with one or more visits at age ≥50 years, and complete data (n 609–617). Repeated assessments on waist circumference (WC) and waist:hip ratio (WHR) were available. Multiple linear mixed models were used to estimate mid-follow-up age central adiposity level and annual rate of change with cut-points set at the sex-specific 80th percentile. The four binary outcomes were: ‘elevated central adiposity’ (ECA-WC and ECA-WHR) and ‘significant increase in central adiposity’ (SICA-WC and SICA-WHR). SNP for VDR (four SNP: (1) rs11568820 (CdX-2:T/C); (2) rs1544410 (BsmI:G/A); (3) rs7975232 (ApaI:A/C); (4) rs731236 (TaqI:G/A)) and Megalin (three SNP: (1) rs3755166:G/A; (2) rs2075252:C/T; (3) rs4668123:C/T) genes were selected. SNP latent classes (SNPLC) and SNP haplotypes (SNPHAP) were created. Multiple logistic regression analyses indicated that, in men, higher ECA-WHR odds were associated with SNPLC Megalin2:rs3755166[–]/rs2075252[TT]/rs4668123[T–] (v. Megalin1:rs3755166[–]/rs2075252[CC]/rs4668123[–]) (OR 2·87; 95 % CI 1·15, 7·12; P = 0·023) and that SNPLC Megalin3:rs3755166[–]/rs2075252[CT]/rs4668123[–] (v. Megalin1) was linked to lower SICA-WC odds (OR 0·48; 95 % CI 0·26, 0·88; P = 0·019) (P > 0·05 for sex × SNPLC). In women, VDR3 SNPHAP (GAA:bAT) was related to lower odds of ECA-WC (OR 0·37; 95 % CI 0·16, 0·87; P = 0·023) (P < 0·05 for sex × SNPHAP), VDR1 SNPHAP (GCA:baT) was associated with greater odds and VDR3 SNPHAP (GAA:bAT) with lower odds of SICA-WC (P > 0·05 for sex × SNPHAP). Vitamin D-related gene polymorphisms were associated with central adiposity status and change. Future mechanistic studies are needed to confirm those polymorphisms' biological significance to central adiposity.

Socioeconomic differences in overweight are well documented, but most studies have only used one or two indicators of socioeconomic position (SEP). The aim of the present study was to explore the relative importance of indicators of SEP (occupation, education and income) in explaining variation in BMI and waist:hip ratio (WHR), and the mediating effect of work control and lifestyle factors (dietary patterns, smoking and physical activity). The Oslo Health Study, a cross-sectional study, was carried out in 2000–1, Oslo, Norway. Our sample included 9235 adult working Oslo citizens, who attended a health examination and filled in two complementary FFQ with < 20 % missing responses to food items. Four dietary patterns were identified through factor analysis, and were named ‘modern’, ‘Western’, ‘traditional’ and ‘sweet’. In multivariate models, BMI and WHR were inversely associated with education (P < 0·001/P < 0·001) and occupation (P = 0·002/P < 0·001), whereas there were no significant associations with income or the work control. The ‘modern’ (P < 0·001) and the ‘sweet’ (P < 0·001) dietary patterns and physical activity level (P < 0·001) were inversely associated, while the ‘Western’ dietary pattern (P < 0·001) was positively associated with both BMI and WHR. These lifestyle factors could not fully explain the socioeconomic differences in BMI or WHR. However, together with socioeconomic factors, they explained more of the variation in WHR among men (21 %) than among women (7 %).