Subsequent Change In Body Mass Index Research Articles

Sex- and Age-Dependent Associations between Parabacteroides and Obesity: Evidence from Two Population Cohort.

Parabacteroides levels are reported to be low in obese individuals, and this genus has shown an anti-obesity capacity in animal studies. Nevertheless, the relationship between Parabacteroides and obesity in different subpopulations, e.g., with respect to age and sex, and its association with subsequent weight change have rarely been explored. The cross-sectional associations of Parabacteroides genus- and species-level OTU abundance with obesity were explored in the Guangdong Gut Microbiome Project (GGMP), which included 5843 adults, and replicated in the Guangzhou Nutrition and Health Study (GNSH), which included 1637 individuals. Furthermore, we assessed the prospective associations of Parabacteroides and its main OTUs' abundance with the subsequent changes in body mass index (BMI) in the GNSH. We found that Parabacteroides was inversely associated with obesity among females and participants aged 40-69 years in the GGMP and the replicated cohort in the GNSH. After a 3-year follow-up, there was no significant correlation between Parabacteroides and the subsequent changes in BMI. However, Seq4172 (P. johnsonii) showed a negative correlation with subsequent BMI changes in the female and middle-aged (40-69 years) subpopulations. Overall, our results indicate that Parabacteroides have an inverse relationship with obesity and that Seq4172 (P. johnsonii) have a negative association with subsequent changes in BMI among females and middle-aged populations in perspective analyses.

Socioeconomic inequalities in the food environment and body composition among school-aged children: a fixed-effects analysis

BackgroundThere is limited evidence regarding socioeconomic inequalities of exposure to the food environment and its contribution to childhood obesity.MethodsWe used data from 4235 children from the Generation R Study, a large birth-cohort conducted in the city of Rotterdam, The Netherlands. We included 11,277 person-observations of body mass index (BMI) and 6240 person-observations of DXA-derived fat mass index (FMI) and fat-free mass index (FFMI) when children were between 4 and 14 years. We applied linear regression models to evaluate changes in the relative and absolute exposure of fast-food outlets, and the healthiness of the food environment within 400 m from home by maternal education. Furthermore, we used individual-level fixed-effects models to study changes in the food environment to changes in BMI, FMI and FFMI.ResultsChildren from lower educated mothers were exposed to more fast-food outlets at any time-point between the age of 4 and 14 years. Over a median period of 7.1 years, the absolute (0.6 fast-food outlet (95% CI: 0.4–0.8)) and relative (2.0%-point (95% CI: 0.7–3.4)) amount of fast-food outlets increased more for children from lower as compared to higher educated mothers. The food environment became more unhealthy over time, but no differences in trends were seen by maternal education level. Changes in the food environment were not associated with subsequent changes in BMI, FMI and FFMI. For children from lower educated mothers not exposed to fast-food at first, we found some evidence that the introduction of fast-food was associated with small increases in BMI.ConclusionsOur findings provide evidence of widening inequalities in exposure to fast-food in an already poor food environment. Access to more fast-food outlets does not seem to have an additional impact on BMI in contemporary contexts with ubiquitous fast-food outlets.

Longitudinal Changes in Arthritis Pain Contribute to Subsequent Changes in Body Mass

Prior studies have documented that body mass index (BMI) is positively associated with bodily pain. However, data on the temporal sequence of BMI and pain suggest mixed results, with some studies indicating a bi-directional relationship, and other research among older adults supporting a uni-directional relationship from BMI to increased pain. Thus, it is critical to further examine temporal dynamics between changes in BMI and changes in bodily pain to help explicate possible mechanisms influencing the relationship. This study evaluated bivariate dynamic models of longitudinal change (McArdle & Hamagami, 2003) in the relationship between BMI and bodily pain with data from older adults participating in the Swedish Adoption/Twin Study of Aging (SATSA). The sample included 858 individuals aged 45-88 at intake, with up to eight waves of follow-up over 26 years. BMI {weight(kg)/[height(m)]2} was evaluated with objective measures of weight and height recorded by a study nurse. Pain symptoms were measured with six self-report pain questions, reflecting two pain factors: (1) pain in neck, back, or shoulder; and (2) hip pain, history of arthritis, or use of arthritis medications. Results indicated that the relationship between BMI and arthritis pain was uni-directional, with changes in pain symptoms contributing to subsequent changes in BMI, but no evidence that changes in BMI contributed to subsequent changes in pain symptoms. Model comparison indicated that the impact of pain on BMI was greatest before age 70, and then reduced somewhat after age 70, when the impact of other factors on BMI (e.g., ill health) likely increases.

Effort-reward imbalance at work and weight changes in a nationwide cohort of workers in Denmark.

ObjectiveTo investigate the relation between effort‐reward imbalance (ERI) at work and subsequent weight changes.MethodsWe included participants from a population‐based cohort of workers in Denmark (mean age = 47 years, 54% women) with two (n = 9005) or three repeated measurements (n = 5710). We investigated the association between (a) ERI (ie, the mismatch between high efforts spent and low rewards received at work) at baseline and weight changes after a 2‐year follow‐up (defined as ≥5% increase or decrease in body mass index (BMI) vs stable), and (b) onset and remission of ERI and subsequent changes in BMI. Using multinomial logistic regression we calculated risk ratios (RR) and 95% confidence intervals (CI), adjusted for sex, age, education, cohabitation, migration background, and follow‐up time.ResultsAfter 2 years, 15% had an increase and 13% a decrease in BMI. Exposure to ERI at baseline yielded RRs of 1.09 (95% CI: 0.95‐1.25) and 1.04 (95% CI: 0.90‐1.20) for the increase and decrease in BMI, respectively. There were no differences between sex and baseline BMI in stratified analyses. The onset of ERI yielded RRs of 1.04 (95% CI: 0.82‐1.31) and 1.15 (95% CI: 0.84‐1.57) for subsequent increase and decrease in BMI. The RRs for the remission of ERI and subsequent increase and decrease in BMI were 0.92 (95% CI: 0.71‐1.20) and 0.78 (95% CI: 0.53‐1.13), respectively. Of the ERI components, high rewards were associated with a lower risk of BMI increase.ConclusionERI was not a risk factor for weight changes. Future studies may investigate whether this result is generalizable to other occupational cohorts and settings.

Routine Cholesterol Tests and Subsequent Change in BMI Among Overweight and Obese Children

IntroductionIn 2011, the National Heart, Lung and Blood Institute and American Academy of Pediatrics concluded that both familial and obesity-associated dyslipidemias increase cardiovascular risk and recommended universal cholesterol testing at ages 9 to 11. It remains unknown whether testing influences body mass index (BMI) trajectory, a key modifiable cardiovascular outcome. MethodsThis quasi-experimental-matched cohort includes children aged 9 to 11 years completing well visits in a diverse primary care network from 2012 to 2014. Participants had baseline BMI ≥85th% and no prior cholesterol testing. Propensity score matching identified untested children similar to tested children on weight measures, practice site, sex, age, race, ethnicity, insurance, and well visit frequency. Change in BMI z-score was assessed over 18 months. Regression adjusted for residual confounding following matching. Data were analyzed in 2018. ResultsMatching improved balance between tested and untested children for all characteristics. The matched cohort of 1808 children was predominantly non-Latino black (48%) or non-Latino white (33%), and Medicaid insured (39%). Baseline BMI z-score was 1.88 for tested and 1.84 for untested children. Of tested children, 25% had cholesterol levels above the 2011 guideline's “acceptable” range. Two children received cholesterol lowering medications. Adjusted analysis found no difference in change in BMI z-score between tested and untested children (0.02, 95% confidence interval −0.01, 0.04). ConclusionsIndividual risk assessment in the form of cholesterol testing is not associated with change in BMI trajectory among overweight and obese children. Though testing may identify familial hypercholesterolemia, results suggest testing does not change BMI trajectory, a key strategy to reduce cardiovascular risk.

Evidence of Bidirectional Associations Between Depressive Symptoms and Body Mass Among Older Adults.

Body fat, measured with body mass index (BMI), and obesity are associated with depressive symptoms. Among younger adults there is stronger evidence of obesity leading to depressive symptoms than of depressive symptoms leading to obesity, but the temporal relationship is unknown among older adults. This study utilized dual-change-score models (DCSMs) to determine the directional relationship between body mass and depressive symptoms among older adults. Participants (n = 1,743) from the Swedish Twin Registry (baseline age range 50-96 years) completed at least one assessment of BMI (nurse measurement of height and weight) and the Center for Epidemiologic Studies-Depression scale (CESD). More than half the sample completed 3 or more assessments, scheduled at intervals of 2-4 years. DCSMs modeled the relationship of BMI and CESD across age, both independently and as part of bivariate relationships. Depressive symptoms contributed to subsequent changes in BMI after age 70, while BMI contributed to subsequent changes in depressive symptoms after age 82. Thus, there is a reciprocal relationship that may change with age. The effect was more pronounced for women. The association of BMI and depressive symptoms is bidirectional among older adults, and it appears to be affected by both age and sex.

Adherence to the Mediterranean dietary pattern and BMI change among US adolescents.

BackgroundAmong adults, the Mediterranean dietary pattern (MDP) is inversely related to body mass index (BMI). Data are lacking on adherence to the MDP among youth in the United States and whether the MDP is related to weight change in that group.ObjectiveTo assess whether adherence to the MDP was associated with BMI change among adolescents. To examine temporality we studied the association between baseline and 2–3 year changes in adherence to the MDP with concurrent changes in BMI, as well as subsequent changes in BMI over a 7-year period.MethodsWe prospectively followed 6 002 females and 4 916 males in the Growing Up Today Study 2, aged 8–15 in 2004, living across the United States. Data were collected by questionnaire in 2004, 2006, 2008, and 2011. Dietary intake was assessed by the Youth/Adolescent Questionnaire. The KidMed Index was derived to measure the adherence to the MDP. We used generalized estimating equations with repeated measures within subjects to assess the association between MDP and BMI change.ResultsA two-point increment in the KidMed Index was independently associated with a lower gain in BMI (−0.04 kg/m2; p=0.001). A greater increase in adherence to the KidMed Index was independently related to a lower gain in BMI in both the concurrent (p-for-trend<0.001) and the subsequent period (p-for-trend=0.002).ConclusionsAdherence to MDP was inversely associated with change in BMI among adolescents. 2-year improvement in adherence to MDP was independently associated with less steep gain in the BMI in both the concurrent and the subsequent period.

Unstable Body Mass Index and Progression to Probable Alzheimer's Disease Dementia in Patients with Amnestic Mild Cognitive Impairment.

We investigated the influence of body mass index (BMI) status at baseline and changes in BMI over a follow-up period on the development of dementia in amnestic mild cognitive impairment (aMCI) patients. The longitudinal data of 747 aMCI patients were used to investigate the relationships among baseline BMI status, subsequent changes in BMI (median follow-up duration: 1.6 years, interquartile range: 1.0-2.3 years), and risk of progression to probable Alzheimer's disease dementia (pADD). The aMCI patients were classified into underweight, normal weight, overweight, and obese subgroups, and further categorized into increased BMI, stable BMI, and decreased BMI subgroups during follow-up using a 4% mean annual change in BMI cut-off value. Compared to the normal weight group, the underweight group had a higher risk of pADD (hazard ratio [HR]: 1.89, 95% confidence interval [CI]: 1.07-3.37) while the obese group had a lower risk (HR: 0.70, 95% CI: 0.49-0.999). After controllingfor baseline BMI status, the decreased BMI (HR: 2.29, 95% CI: 1.41-3.72) and increased BMI (HR: 3.96, 95% CI: 2.62-6.00) groups were at increased risk of progression to pADD. Our findings suggested that underweight at baseline was associated with a higher risk of progression to pADD, while obesity at baseline predicted a lower risk. Furthermore, significant changes in BMI during the follow-up period reflected an increased risk of progression to pADD, regardless of BMI status at baseline.

Association between body mass index and caries among children and adolescents

The aim of this article was to examine the relationship between childhood caries, body mass index (BMI) and subsequent changes in BMI over 6 years, and to investigate whether these associations were modified by social class. Data were from the European Youth Heart Study (EYHS) merged with data on caries experience from the Danish National Board of Health, (SCOR register). At baseline, 26.2% of the children/adolescents were caries free and 39% at follow-up. A larger percentage of normal weight children/adolescents were caries free, compared with the overweight/obese group of children/adolescents. The linear regression analysis showed that childhood caries was generally not associated with either BMI or subsequent changes in BMI. However, among children whose mothers were well educated, there was an inverse association between caries at baseline and subsequent changes in BMI over a period of 6 years, for example, a high caries experience was associated with a smaller increment in BMI, compared with the group of children with a low caries experience. No association was found for those with lower SES. An inverse association between caries and subsequent changes in BMI was found, but only among children with well-educated mothers, suggesting that high caries experience may be a marker for low future risk of overweight among the more advantaged. Associations did not appear to be significant among the less advantaged; however, numbers in this group were low, and an association may have been overlooked. Hence, more studies are needed to confirm these findings.

Association between sweet drink intake and adiposity in Danish children participating in a long‐term intervention study

In some previous studies direct associations between intake of soft drinks, sugar-sweetened beverages and adiposity have been reported. The majority of these studies were, however, conducted in the USA and it is uncertain if the results are applicable to non-US countries. To assess the association between sweet drink intake at age 6 and 9 years and the subsequent 3- to 7-year changes in body mass index (BMI) and sum of four skin-folds (Σ4SF). Information on sweet drink intake (7 days food record) and physical activity (accelerometer) was obtained at age 6 years (n = 366) [Correction made here after initial online publication.] and 9 years (n = 269). Weight, height and Σ4SF were measured at age 6, 9 and 13 years. Additional information on socio-economic status, maternal BMI and pubertal status was obtained. No associations were observed between sweet drink intake at age 6 years and change in BMI or logΣ4SF from age 6 to 9 years or 6 to 13 years. Also, no associations were observed between change in sweet drink intake from age 6 to 9 years and subsequent change in BMI or logΣ4SF from age 9 to 13 years. A weak direct association was observed between sweet drink intake at age 9 years and change in logΣ4SF from age 9 to 13 years (per 100 g ∼ 3.38 fl oz) (β: 0.014, 95% confidence interval [CI]: -0.001 to 0.029, P = 0.06), while no association was seen for BMI. In supplementary analyses a similar association was observed for soft drinks (β: 0.087, 95% CI: 0.048 to 0.126, P = 0.001) but only in the intervention group. We observed associations between intake of sweet drinks and soft drinks and change in skin-fold thickness in a group of Danish children. However, as the associations did not remain significant when multiple testing was considered or was only significant among children from the intervention group, the results do not confirm or refute the direct association reported in previous studies.

Socio-demographic variables and 6 year change in body mass index: longitudinal results from the GLOBE study.

Body mass index (BMI) differs by socio-demographic variables, but the origin of these associations remains relatively unknown. To investigate the association between socio-demographic variables and the subsequent change in BMI over six years. A Dutch prospective cohort study (GLOBE) from which data were used from initially 20-49-year-old subjects (males: n=362; females: n=405). BMI was calculated from self-reported body height and weight data obtained in 1991 and 1997. Socio-demographic variables used were sex, age, educational level and the occupational level of the main breadwinner, family income, marital status, religious affiliation and degree of urbanization and measured in 1991. Cross-sectionally, BMI was higher in males than in females. BMI was positively associated with age and negatively associated with educational level in both sexes, after adjustment for the other socio-demographic variables. A positive association of BMI with family income was found in males and a negative association with occupational level was found in females. During follow-up, BMI increased significantly more in females (from 23.0 (s.d. 3.3) to 24. 2 (s.d. 3.8)) than in males (from 24.3 (s.d. 2.9) to 25.1 (s.d. 3. 5)). With the exception of a significant lesser increase in BMI in initially 30-39-year-old women compared to initially 40-49-year-old women, no other statistically significant associations were found between socio-demographic variables and the 6-year change in BMI. Cross-sectional differences in BMI by socio-demographic variables are not due to different 6-year changes in BMI for categories of these variables in adulthood. Cross-sectional differences in BMI by educational level are probably established at the end of adolescence.