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To conduct nutrition-related analyses on large-scale health surveys, two aspects of the survey must be incorporated into the analysis: the sampling weights and the sample design; a practice which is not always observed. The present paper compares three analyses: (1) unweighted; (2) weighted but not accounting for the complex sample design; and (3) weighted and accounting for the complex design using replicate weights.
Descriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.
Cross-sectional health survey with complex sample design where replicate weights are supplied rather than the variables containing sample design information.
Responding adults from the National Nutrition and Physical Activity Survey (NNPAS) part of the Australian Health Survey (2011–2013).
Unweighted analysis produces biased estimates and incorrect estimates of se. Adjusting for the sampling weights gives unbiased estimates but incorrect se estimates. Incorporating both the sampling weights and the sample design results in unbiased estimates and the correct se estimates. This can affect interpretation; for example, the incorrect estimate of the OR for being a current smoker in the unweighted analysis was 1·20 (95 % CI 1·06, 1·37), t= 2·89, P = 0·004, suggesting a statistically significant relationship with being overweight/obese. When the sampling weights and complex sample design are correctly incorporated, the results are no longer statistically significant: OR = 1·06 (95 % CI 0·89, 1·27), t = 0·71, P = 0·480.
Correct incorporation of the sampling weights and sample design is crucial for valid inference from survey data.
Altered gut microbial ecology contributes to the development of metabolic diseases including obesity. However, studies based on different populations have generated conflicting results due to diet, environment, methodologies, etc. The aim of our study was to explore the association between gut microbiota and Body Mass Index (BMI) in Chinese college students. 16S next-generation sequencing (NGS) was used to test the gut microbiota of 9 lean, 9 overweight/obesity, and 10 normal-weight male college students. The differences of gut microbiota distribution among three groups were compared, and the relationship between the richness, diversity, composition of gut microbiota and BMI were analyzed. The predominant phyla Bacteroidetes and Firmicutes were further confirmed by real-time PCR. Metagenomic biomarker discovery was conducted by Linear discriminant analysis (LDA) Effect Size (LEfSe). NGS revealed that gut microbiota composition was different among three groups, but there was no difference in the abundance ratio of Firmicutes/ Bacteroidetes. Several bacterial taxa were in linear relationship with BMI (positive relationship: uncultured bacterium (Bacteroides genus); negative relationship: Porphyromonadaceae, Acidaminococcaceae, Rikenellaceae, Desulfovibrionaceae, Blautia, Anaerotruncus, Parabacteroides, Alistipes). Moreover, gut microbiota diversity decreased with the increase of BMI. And LEfSe analyze indicated that Blautia, Anaerotruncus and its uncultured species were significantly enriched in the lean group (LDA score≥3), Parasuterella and its uncultured species were significantly enriched in the overweight/obese groups(LDA score≥3). In general, gut microbiota composition and microbial diversity were associated with BMI in Chinese male college students. Our results might enrich the understanding between gut microbiota and obesity.
Processed foods and fatty, sugary snacking products, such as fizzy drinks and desserts, have become more popular, causing a desire to replace meals with snacks worldwide. High-sugar and fat-rich food components have been reported to be associated with increased level of dental caries as well as underweight and overweight. The aim of the present cross-sectional population-based study was to analyse the eating behaviours of young, healthy Finnish males in association with oral health and BMI, considering self-reported and residential background factors.
Finnish Defence Forces, Finland.
The used clinical data were gathered from 13 564 Finnish conscripts born in the beginning of the 1990s through clinical check-ups. In addition, about 8700 of the conscripts answered a computer-assisted questionnaire (‘Oral Health of the Conscripts 2011’ data) about their background information and health habits.
There was distinct variation in dietary patterns. Eating breakfast, regular physical exercise and daily tooth brushing all decreased the odds for restorative dental treatment need (decayed teeth), whereas smoking and drinking fizzy drinks for quenching thirst increased it. Eating breakfast and dinner were each associated with lower BMI, but smoking increased the odds for higher BMI (≥25 kg/m2).
Regular, proper meals and especially eating breakfast decreased the odds for both dental caries and high BMI (≥25 kg/m2).
The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.
We use household scanner data, paired with rich demographics and merged with self-reported measures of obesity and body mass index (BMI), to investigate the potential effects of fruit and vegetable purchasing behavior on adult obesity and body weight. We find that increasing household fruit and vegetable expenditure shares by one percentage point decreases the multiyear incidence of adult obesity by approximately 9 percent and average adult BMI by 1.4 percent, controlling for a host of potential confounding factors and measures of lifestyle choices. The results are robust to specification choice, although estimated impacts differ by gender. Our findings help quantify the potential impacts of government efforts aimed at increasing fruit and vegetable intake.
Dietary behaviour is influenced by a complex web of biological, psychological, physiological, social, economic and cultural factors. Understanding socio-demographic and anthropometric characteristics that influence food choice may be important in guiding dietary interventions. The present study aimed to identify whether socio-demographic and anthropometric characteristics influence food choice in an Irish working population. A cross-sectional survey was conducted in 2014 as part of the Food Choice at Work Study, a large clustered non-randomised, controlled trial based in county Cork, Ireland. Information regarding food motives was collected at the 3–4 months follow-up. The ‘Food Choice Questionnaire’ was used to measure food motives. Multiple linear regression was conducted to test the association between socio-demographic and anthropometric characteristics (age, sex, BMI, education, type of accommodation, living situation, marital status, parental status) and worksite and food motives. A total of 678 employees were included in the analysis. Overall, only a small percentage of food choice was influenced by the characteristics included in this analysis (1·6 to 8·8 %). Sensory appeal and satisfaction were scored most important by all sub-populations. Sex was most often associated with differences in food motives (i.e. all food motives except for familiarity and ethical concern were significantly more important to females compared with males; P = 0·001/P < 0·001). Worksite, age, BMI and marital status also seemed to play a small role in influencing food choice. The results show that food choice is complex and not easily explained by differences in socio-demographic or anthropometric population characteristics.
Previous research has implicated demographic, psychological, behavioral, and cognitive variables in the onset and maintenance of pediatric overweight/obesity. No adequately-powered study has simultaneously modeled these variables to assess their relative associations with body mass index (BMI; kg/m2) in a nationally representative sample of youth.
Multiple machine learning regression approaches were employed to estimate the relative importance of 43 demographic, psychological, behavioral, and cognitive variables previously associated with BMI in youth to elucidate the associations of both fixed (e.g. demographics) and potentially modifiable (e.g. psychological/behavioral) variables with BMI in a diverse representative sample of youth. The primary analyses consisted of 9–10 year olds divided into a training (n = 2724) and test (n = 1123) sets. Secondary analyses were conducted by sex, ethnicity, and race.
The full sample model captured 12% of the variance in both the training and test sets, suggesting good generalizability. Stimulant medications and demographic factors were most strongly associated with BMI. Lower attention problems and matrix reasoning (i.e. nonverbal abstract problem solving and inductive reasoning) and higher social problems and screen time were robust positive correlates in the primary analyses and in analyses separated by sex.
Beyond demographics and stimulant use, this study highlights abstract reasoning as an important cognitive variable and reaffirms social problems and screen time as significant correlates of BMI and as modifiable therapeutic targets. Prospective data are needed to understand the predictive power of these variables for BMI gain.
Within- and across-country nutritional disparities were examined among older adults in six different countries at varying levels of development.
Older adults (aged 50 years or over) in China, Ghana, India, Mexico, Russia and South Africa using the Study on global AGEing and adult health (SAGE).
While the distribution of BMI categories varied by country, development-related characteristics were generally related to BMI category in a similar way: urban-living, educated and wealthier individuals were typically more likely to be in a higher BMI category. However, there were some exceptions that corroborate findings in more developed countries. Indeed, a pooled partial proportional odds model which included gross domestic product per capita interactions made the case for intertwining processes of development and the nutrition transition.
Population segments to be targeted by nutrition policy and programme implementation might need to change over the course of development.
The present study evaluated the association of two measures of diet quality
with BMI and waist circumference (WC), overall and by education level, among
Mexican men and women.
We constructed two a priori indices of diet quality, the
Mexican Diet Quality Index (MxDQI) and the Mexican Alternate Healthy Eating
Index (MxAHEI), which we examined relative to BMI and WC. We computed
sex-specific multivariable linear regression models for the total sample and
by education level.
Mexican men (n 954) and women (n 1356)
participating in the Mexican National Health and Nutrition Survey 2012.
Total dietary scores were not associated with BMI in men and women, but total
MxDQI was inversely associated with WC in men (−0·10, 95 % CI
−0·20, −0·004 cm). We also found that some
results differed by education level in men. For men with the lowest
education level, a one-unit increase in total MxDQI and MxAHEI score was
associated with a mean reduction in BMI of 0·11 (95 % CI
−0·18, 0·04) and 0·18 (95 % CI
−0·25, −0·10) kg/m2, respectively.
Likewise, a one-unit increase in total MxDQI and MxAHEI score was associated
with a mean change in WC of −0·30 (95 % CI
−0·49, −0·11) and −0·53 (95 % CI
−0·75, −0·30) cm, respectively, in men with the
lowest level of education. In women, the association of diet quality scores
with BMI and WC was not different by education level.
Our findings suggest that a higher diet quality in men with low but not high
education is associated with lower BMI and WC.
(i) To assess diagnostic accuracy of mid-upper arm circumference (MUAC) for screening thinness and severe thinness in Indian adolescent girls aged 10–14 and 15–19 years compared with BMI-for-age Z-score (BAZ) <−2 and <−3 as the gold standard and (ii) to identify appropriate MUAC cut-offs for screening thinness and severe thinness in Indian girls aged 10–14 and 15–19 years.
Cross-sectional, conducted October 2016–April 2017.
Four tribal blocks of two eastern India states, Chhattisgarh and Odisha.
Girls (n 4628) aged 10–19 years. Measurements included height, weight and MUAC to calculate BAZ. Standard diagnostic accuracy tests, receiver–operating characteristic curves and Youden index helped arrive at MUAC cut-offs at BAZ < −2 and <−3, as gold standard.
Mean MUAC and BMI correlation was positive (0·78, P = 0·001 and
r2 = 0·61). Among 10–14 years, MUAC cut-off corresponding to BAZ < −2 and BAZ < −3 was ≤19·4 and ≤18·9 cm. Among 15–19 years, corresponding values were ≤21·6 and ≤20·7 cm. For both BAZ < −2 and BAZ < −3, specificity was higher in 15–19 v. 10–14 years. State-wise variations existed. MUAC cut-offs ranged from 17·7 cm (10 years) to 22·5 cm (19 years) for BAZ < −2, and from 17·0 cm (10 years) to 21·5 cm (19 years) for BAZ < −3. Single-age area under the curve range was 0·82–0·97.
Study provides a case for use of year-wise and sex-wise context-specific MUAC-cut-offs for screening thinness/severe thinness in adolescents, rather than one MUAC cut-off across 10–19 years, depending on purpose and logistic constraints.
To assess the strength of correlation and agreement between mid-upper arm circumference (MUAC) and BMI, and determine suitable MUAC cut-offs, to detect wasting and severe wasting among non-pregnant adult women in India.
Cross-sectional studies were conducted in five high-burden pockets of four Indian states.
Prevalence of malnutrition among women and children is very high in these pockets and the government plans to implement community-based pilot projects to address malnutrition in these areas.
Anthropometric measurements were carried out on 1716 women with children <5 years of age. However, analyses were conducted on 1538 non-pregnant adult women.
The results showed a strong correlation between MUAC and BMI in the non-pregnant women, with correlation coefficient of 0·860 (95 % CI 0·831, 0·883; P < 0·001). Cohen’s κ of 0·812 and 0·884 also showed good agreement between MUAC and BMI in identifying maternal wasting and severe wasting, respectively. The univariate regression model between MUAC and BMI explained 0·734 or 73 % of the variation in BMI. The MUAC cut-offs for wasting (BMI < 18·5 kg/m2) and severe wasting (BMI < 16·0 kg/m2) were calculated as 232 and 214·5 mm, respectively.
MUAC is a strong predictor of maternal BMI among non-pregnant women with children <5 years in high-burden pockets of four Indian states. In a resource-constrained setting where BMI may not be feasible, the MUAC cut-offs could reliably be used to screen wasting and severe wasting in non-pregnant women for providing appropriate care.
To identify cut-off points for waist circumference (WC), waist-to-height ratio (WHtR) and BMI associated with hypertension in the Brazilian adult and elderly population.
Cross-sectional study. The receiver-operating characteristic (ROC) curve was used to determine the cut-off points of WC, WHtR and BMI in the prediction of hypertension. Those who had systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg and those who reported use of antihypertensive medication were considered hypertensive.
Participants from the National Health Survey, the Brazilian household-based survey conducted in 2013, of both sexes and age ≥20 years.
Cut-off points for WC and WHtR increased with age in both sexes. WC cut-off limits ranged between 88·0 and 95·9 cm in men and between 85·0 and 93·2 cm in women. For WHtR, cut-off scores ranged from 0·51 to 0·58 for men and from 0·53 to 0·61 for women. Additionally, the area under the ROC curve (AUC) for all age and sex groups was greater than 0·60 while the lower limit of the AUC 95 % CI for both WC and WHtR was not less than 0·50. The performance of BMI was similar to that of indicators of fat location.
All analysed anthropometric indicators had similar performance in identifying hypertension in the Brazilian population.
The association between gestational weight gain (GWG) and exclusive breast-feeding (EBF) practices remains unclear. The present study evaluated the association between GWG and EBF in the first 6 months postpartum among primiparas in rural China.
The study population was drawn from a previous randomized controlled trial, and the relevant data were obtained from an electronic, population-based perinatal system and a monitoring system for child health care. GWG was categorized according to the guidelines of the Institute of Medicine.
Five rural counties in Hebei Province, China.
A total of 8449 primiparas.
Of the women, 58·7 % breast-fed exclusively for the first 6 months postpartum. Overweight women who gained either more or less weight than the recommended GWG tended to experience failure of EBF (OR=0·49; 95 % CI 0·34, 0·70; P<0·001 and OR=0·79; 95 % CI 0·63, 0·99; P=0·048, respectively). The same results were also observed among obese women; the OR for lower and greater weight gain were 0·28 (95 % CI 0·08, 0·94; P=0·04) and 0·55 (95 % CI 0·32, 0·95; P=0·03), respectively.
GWG that is below or above the Institute of Medicine recommendations is associated with EBF behaviour for the first 6 months postpartum in overweight and obese primiparas in rural China.
Limited information is available on the prevalence and effect of hypertriglyceridaemic–waist (HTGW) phenotype on the risk of type 2 diabetes mellitus (T2DM) in rural populations.
In the present cross-sectional study, we investigated the prevalence of the HTGW phenotype and T2DM and the strength of their association among rural adults in China.
HTGW was defined as TAG >1·7 mmol/l and waist circumference (WC) ≥90 cm for males and ≥80 cm for females. Logistic regression analysis yielded adjusted odds ratios (aOR) relating risk of T2DM with HTGW.
Adults (n 12 345) aged 22·83–92·58 years were recruited from July to August of 2013 and July to August of 2014 from a rural area of Henan Province in China.
The prevalence of HTGW and T2DM was 23·71 % (males: 15·35 %; females: 28·88 %) and 11·79 % (males: 11·15 %; females: 12·18 %), respectively. After adjustment for sex, age, smoking, alcohol drinking, blood pressure, physical activity and diabetic family history, the risk of T2DM (aOR; 95 % CI) was increased with HTGW (v. normal TAG and WC: 3·23; CI 2·53, 4·13; males: 3·37; 2·30, 4·92; females: 3·41; 2·39, 4·85). The risk of T2DM with BMI≥28·0 kg/m2, simple enlarged WC and simple disorders of lipid metabolism showed an increasing tendency (aOR=1·31, 1·75 and 2·32).
The prevalence of HTGW and T2DM has reached an alarming level among rural Chinese people, and HTGW is a significant risk factor for T2DM.
Worldwide data indicate a growing number of energy homeostasis disorders, which are especially dangerous in childhood. The distribution and growing trends of overweight and obesity in children have been widely investigated, unlike the prevalence of too-low body weight and its determinants. This study aimed to estimate the frequency of body mass deficiency in Polish rural girls and differences among four Polish regions – Choszczno and Leszno in the north-west, and Ostrów Mazowiecka and Suwałki in the north-east. Data were taken from 7764 rural girls aged 9–18 years examined in 1987, when the country was in economic crisis, and 9431 such girls examined in 2001, when the country was undergoing political transformation. The frequency of weight deficiency was estimated based on BMI by applying the international standards of Cole. An Extent of Overweight (EOW) index was used to create an Extent of Thinness (EOT) index. A significant increase in weight deficiency was found in the rural girls – from 7.5% in 1987 to 8.9% in 2001 – and an increase in the EOT index from 0.37 in 1987 to 0.43 in 2001. Analysis by area of residence demonstrated significant differentiation. In the regions in north-west Poland, mainly inhabited by non-farming families, the prevalence of weight deficiency in girls almost doubled from 1987 to 2001, probably because of the mass and long-term unemployment that resulted from the closure of state farms in 1992. In contrast, in the north-east regions, the prevalence of weight deficiency remained almost unchanged over this period, with only a slight decrease, probably because the inhabitants were mainly farm and farm/working families with better living conditions. Despite the overall increase in thinness prevalence in rural girls in Poland, different living conditions have had different biological effects.
Previous research stresses the importance of social networks for obesity. We draw on friendship data from 18,133 adolescents in four European countries to investigate the relationship between individuals’ body mass index (BMI) and the BMI of their friends. Our study reveals strong evidence for BMI clustering in England, Germany, the Netherlands, and Sweden; adolescents tend to be friends with others who have a similar BMI. Furthermore, we extend current debate and explore friendship characteristics that moderate the relationship between social networks and BMI. We demonstrate that BMI clustering is more pronounced in (1) strong compared to weak friendships and (2) between adolescents of the same biological sex. These findings indicate thatmore research on social networks and health is needed which distinguishes between different kinds of relationships.
Observational studies suggest that breast-feeding is associated with a more favourable BMI and cardio-metabolic markers, but potential underlying mechanisms are unclear. As serum adiponectin has an important function in adults for glucose and lipid metabolism, we assessed 251 participants of the Prevention and Incidence of Asthma and Mite Allergy birth cohort whether breast milk adiponectin is associated with childhood BMI and cardio-metabolic markers. We measured adiponectin levels in breast milk collected around 3 months after birth of the child and subsequently obtained weight and height repeatedly up to the age of 17 years. A medical examination (including blood pressure, glycated Hb and cholesterol) was performed at the age of 8, 12 and 16 years. We used multivariable mixed models to assess the association between breast milk adiponectin and BMI and cardio-metabolic markers at these ages. In models adjusted for exact age of breast milk collection, maternal age, presence of siblings, maternal BMI, pregnancy weight gain and child’s birth weight, each unit increase in log breast milk adiponectin (in ng/ml) was associated with a 0·28 lower BMI z score (95 % CI –0·56, 0·00) at 3 months. After the age of 1 year, there was a tendency towards a higher BMI z score with increased breast milk adiponectin at some ages, but this pattern was not consistent throughout childhood. There were no associations between breast milk adiponectin and any of the cardio-metabolic markers in childhood. We conclude that in our study with follow-up until 17 years of age, breast milk adiponectin has no long-term effect on BMI and cardio-metabolic health during childhood.
The aim of the present study was to compare selected obesity indicators with comprehensive health status.
The study employed a pooled cross-sectional design.
BMI, waist circumference, waist-to-height ratio (WHtR) and body fat percentage were considered as indirect obesity indicators. The Edmonton Obesity Staging System (EOSS) was used as a composite indicator to comprehensively reflect obesity-related co-morbidities. Cohen’s κ coefficient was used to evaluate inter-measurement agreement for obesity. Conformity of indirect obesity indicators to the EOSS was assessed based on percentage agreement (proportion classified as obese and severely unhealthy as a result of obesity among the total sample), sensitivity (proportion classified as obese among individuals severely unhealthy as a result of obesity) and specificity (proportion classified as non-obese among fairly healthy individuals). Logistic regression analysis was used to identify the sociodemographic factors most strongly associated with conformity.
The study included 17338 adults from the Korea National Health and Nutrition Examination survey conducted between July 2008 and May 2011.
Level of conformity to the EOSS was highest for WHtR (60·77 %) and lowest for BMI (35·96 %). WHtR and BMI had the highest sensitivity (53·7 %) and specificity (98·4 %), respectively. Predictability of conformity was lower among men for all indirect obesity indicators.
WHtR has the greatest potential to identify individuals at risk of health problems due to obesity. Individual demographic factors must be considered in selecting the most appropriate obesity measurement.
To develop a new predictive equation for fat mass percentage (%FM) based on anthropometric measurements and to assess its ability to discriminate between obese and non-obese individuals.
Adults (n 275; 181 women) aged 20–63 years with BMI between 17·4 and 42·4 kg/m2.
Thirty-seven per cent of our sample was obese using %FM measured by air-displacement plethysmography (BOD POD®; Life Measurement Instruments). The fat mass was computed from the difference between weight and fat-free mass (FFM). FFM was estimated using an equation obtained previously in the study from weight, height and sex of the individuals. The %FM estimated from the obtained FFM showed a sensitivity of 90·3 (95 % CI 86·8, 93·8) % and a specificity of 58·0 (95 % CI 52·1, 63·8) % in the diagnosis of obesity. Ninety-three per cent of participants with obesity and 65 % of participants without obesity were correctly classified.
The anthropometry-based equation obtained in the present study could be used as a screening tool in clinical and epidemiological studies not only to estimate the %FM, but also to discriminate the obese condition in populations with similar characteristics to the participant sample.
To assess the reliability and validity of body weight (BW) and body image (BI) perception reported by parents (in children) and by adolescents in a South American population.
Cross-sectional study. BW perception was evaluated by the question, ‘Do you think you/your child are/is: severely wasted, wasted, normal weight, overweight, obese?’ BI perception was evaluated using the Gardner scale. To evaluate reliability, BW and BI perceptions were reported twice, two weeks apart. To evaluate validity, the BW and BI perceptions were compared with WHO BMI Z-scores. Kappa and Kendall’s tau-c coefficients were obtained.
Public and private schools and high schools from six countries of South America (Argentina, Peru, Colombia, Uruguay, Chile, Brazil).
Children aged 3–10 years (n 635) and adolescents aged 11–17 years (n 400).
Reliability of BW perception was fair in children’s parents (κ=0·337) and substantial in adolescents (κ=0·709). Validity of BW perception was slight in children’s parents (κ=0·176) and fair in adolescents (κ=0·268). When evaluating BI, most children were perceived by parents as having lower weight. Reliability of BI perception was slight in children’s parents (κ=0·124) and moderate in adolescents (κ=0·599). Validity of BI perception was poor in children’s parents (κ=−0·018) and slight in adolescents (κ=0·023).
Reliability of BW and BI perceptions was higher in adolescents than in children’s parents. Validity of BW perception was good among the parents of the children and adolescents with underweight and normal weight.