Structural equation modeling of food craving across the menstrual cycle using behavioral, neuroendocrine, and metabolic factors.
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ABSTRACT:
SUBMITTER: Krishnan S
PROVIDER: S-EPMC6251416 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Publications
Structural equation modeling of food craving across the menstrual cycle using behavioral, neuroendocrine, and metabolic factors.
Krishnan Sridevi S Agrawal Karan K Tryon Rebecca R RR Welch Lucas C LC Horn William F WF Newman John W JW Keim Nancy L NL
Physiology & behavior 20180718
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Project description:At least 282 Food Policy Councils (FPCs) are currently working to improve access to healthy foods in their communities by connecting food system sectors, gathering community input, and advising food policy. Empirical research on FPCs is limited. This study empirically evaluates FPCs to better understand the relationships between Organizational Capacity, Social Capital, and Council Effectiveness by testing a FPC Framework adapted from Allen and colleagues (2012). Members of all FPCs in the U.S., Canada, and Native American Tribes and First Nations were invited to complete the Food Policy Council Self-Assessment Tool (FPC-SAT). Structural equation modeling was used to test the FPC Framework. Three hundred and fifty-four FPC members from 95 councils completed the FPC-SAT. After slight modification, a revised FPC Framework was a good fit with the data (?2 = 40.085, df = 24, p-value = .021, comparative fit index = 0.988, Tucker Lewis index = 0.982, root mean squared error of approximation = 0.044, p-close = .650). A moderation analysis revealed that community context influences the relationship between Social Capital and Council Effectiveness within the FPC Framework. The FPC Framework can guide capacity building interventions and FPC evaluations. The empirically tested framework can help FPCs efficiently work toward achieving their missions and improving their local food system.
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Project description:BackgroundAlthough the consequences of food insecurity on physical health and nutritional status of youth living have been reported, its effect on their mental health remains less investigated in developing countries. The aim of this study was to examine the pathways through which food insecurity is associated with poor mental health status among youth living in Ethiopia.MethodsWe used data from Jimma Longitudinal Family Survey of Youth (JLFSY) collected in 2009/10. A total of 1,521 youth were included in the analysis. We measured food insecurity using a 5-items scale and common mental disorders using the 20-item Self-Reporting Questionnaire (SRQ-20). Structural and generalized equation modeling using maximum likelihood estimation method was used to analyze the data.ResultsThe prevalence of common mental disorders was 30.8% (95% CI: 28.6, 33.2). Food insecurity was independently associated with common mental disorders (β = 0.323, P<0.05). Most (91.8%) of the effect of food insecurity on common mental disorders was direct and only 8.2% of their relationship was partially mediated by physical health. In addition, poor self-rated health (β = 0.285, P<0.05), high socioeconomic status (β = -0.076, P<0.05), parental education (β = 0.183, P<0.05), living in urban area (β = 0.139, P<0.05), and female-headed household (β = 0.192, P<0.05) were associated with common mental disorders.ConclusionsFood insecurity is directly associated with common mental disorders among youth in Ethiopia. Interventions that aim to improve mental health status of youth should consider strategies to improve access to sufficient, safe and nutritious food.
| S-EPMC5113011 | biostudies-literature
Project description:BackgroundMenstrual disorders, influenced by dietary habits like high fat intake and low fruit and vegetable consumption, are a global public health issue. This study assessed the prevalence of dysmenorrhea, premenstrual syndrome (PMS), and irregular menstrual cycle (IMC) among female university students in Bangladesh, focusing on food cravings and low vitamin A intake as risk factors.MethodsIn this comprehensive study, data from randomly selected female university students were collected using a structured questionnaire. The associations were analyzed through chi-square tests and multivariable logistic regression, reported as adjusted odds ratios (AOR).ResultsThe most prevalent menstrual disorder was dysmenorrhea (68.3%) followed by PMS (33.8%), and IMC (24.3%). Food cravers for high-fat and sweet foods were likely to experience dysmenorrhea (AOR: 2.4, 95% CI: 1.5-3.9, P<0.001), suffer from PMS (AOR: 3.9, 95% CI: 2.3-6.6, P<0.001), and have IMC (AOR: 3.0, 95% CI: 1.6-5.3, P<0.001) vs. subjects who didn't. Subjects consuming vitamin A-rich plant foods had 40% (AOR: 0.6, 95% CI: 0.4-0.9, P < 0.01) and 60% (AOR: 0.4, 95% CI: 0.2-0.6, P<0.001) less likely suffering from dysmenorrhea and IMC vs. who didn't. Both underweight and overweight/obese subjects experienced more than 2-fold dysmenorrhea vs. normal-weight peers. The chance of IMC was nearly 3-fold among overweight/obese subjects. However, lower physical activity was associated with PMS and IMC whereas family history was associated with dysmenorrhea and PMS. Among the socio-demographic factors, maternal education, place of residence, and earlier menarche (≤12 years) were associated with dysmenorrhea while marital status was associated with IMC.ConclusionThis study indicates that increasing the intake of vitamin A-rich plant foods and reducing high-fat, sweet foods can lower the risk of dysmenorrhea and IMC. Additionally, it highlights the need for regular exercise to mitigate the increased risk of PMS and IMC.
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Project description:College students are one of the most at-risk population groups for food poisoning, due to risky food safety behaviors. Using the Likert Scale, undergraduate students were asked to participate in a Food Safety Survey which was completed by 499 students ages 18-25. Data was analyzed using SPSS and AMOS statistical software. Four conceptual definitions regarding food safety were defined as: general food safety, bacterial food safety, produce food safety, and politics associated with food safety. Knowledge seems to be an important factor in shaping students attitudes regarding general and bacterial safety. Ethnicity plays a role in how people view the politics of food safety, and the safety of organic foods.
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Project description:Externalizing behaviors encompass manifestations of risk-taking, self-regulation, aggression, sensation-/reward-seeking, and impulsivity. Externalizing research often includes substance use (SU), substance use disorder (SUD), and other (non-SU/SUD) "behavioral disinhibition" (BD) traits. Genome-wide and twin research have pointed to overlapping genetic architecture within and across SUB, SUD, and BD. We created single-factor measurement models-each describing SUB, SUD, or BD traits--based on mutually exclusive sets of European ancestry genome-wide association study (GWAS) statistics exploring externalizing variables. We then applied trivariate Cholesky decomposition to these factors in order to identify BD-specific genomic variation and assess the partitioning of BD's genetic covariance with each of the other facets. Even when the residuals for indicators relating to the same substance were correlated across the SUB and SUD factors, the two factors yielded a large zero-order correlation (rg=.803). BD correlated strongly with the SUD (rg=.774) and SUB factors (rg=.778). In our initial decompositions, 33% of total BD variance remained after removing variance associated with SUD and SUB. The majority of covariance between BD and SU and between BD and SUD was shared across all factors. When only nicotine/tobacco, cannabis, and alcohol were included for the SUB/SUD factors, their zero-order correlation increased to rg=.861; in corresponding decompositions, BD-specific variance decreased to 27%. In summary, BD, SU, and SUD were highly genetically correlated at the latent factor level, and a significant minority of genomic BD variation was not shared with SU and/or SUD. Further research can better elucidate the properties of BD-specific variation by exploring its genetic/molecular correlates.
| S-EPMC10925358 | biostudies-literature
Project description:The menstrual cycle is an essential life rhythm governed by interacting levels of progesterone, estradiol, follicular stimulating, and luteinizing hormones. To study metabolic changes, biofluids were collected at four timepoints in the menstrual cycle from 34 healthy, premenopausal women. Serum hormones, urinary luteinizing hormone and self-reported menstrual cycle timing were used for a 5-phase cycle classification. Plasma and urine were analyzed using LC-MS and GC-MS for metabolomics and lipidomics; serum for clinical chemistries; and plasma for B vitamins using HPLC-FLD. Of 397 metabolites and micronutrients tested, 208 were significantly (p < 0.05) changed and 71 reached the FDR 0.20 threshold showing rhythmicity in neurotransmitter precursors, glutathione metabolism, the urea cycle, 4-pyridoxic acid, and 25-OH vitamin D. In total, 39 amino acids and derivatives and 18 lipid species decreased (FDR < 0.20) in the luteal phase, possibly indicative of an anabolic state during the progesterone peak and recovery during menstruation and the follicular phase. The reduced metabolite levels observed may represent a time of vulnerability to hormone related health issues such as PMS and PMDD, in the setting of a healthy, rhythmic state. These results provide a foundation for further research on cyclic differences in nutrient-related metabolites and may form the basis of novel nutrition strategies for women.
| S-EPMC6167362 | biostudies-literature
Project description:Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in humans. This approach is valuable in studies to better understand complex human biological systems which may be involved in diseases and hence, have potential clinical relevance. In order to achieve this, it is necessary to infer gene interactions that are not directly observed (i.e. latent or hidden) by way of structural equation modeling (SEM) on the expression levels or activities of the downstream targets of regulator genes. Here we developed an R Shiny application, termed "Structural Equation Modeling of In silico Perturbations (SEMIPs)" to compute a two-sided t-statistic (T-score) from analysis of gene expression data, as a surrogate to gene activity in a given human specimen. SEMIPs can be used in either correlational studies between outcome variables of interest or subsequent model fitting on multiple variables. This application implements a 3-node SEM model that consists of two upstream regulators as input variables and one downstream reporter as an outcome variable to examine the significance of interactions among these variables. SEMIPs enables scientists to investigate gene interactions among three variables through computational and mathematical modeling (i.e. in silico). In a case study using SEMIPs, we have shown that putative direct downstream genes of the GATA Binding Protein 2 (GATA2) transcription factor are sufficient to infer its activities in silico for the conserved progesterone receptor (PGR)-GATA2-SRY-box transcription factor 17 (SOX17) genetic network in the human uterine endometrium.
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Project description:Craving is considered a key characteristic of diverse pathologies, but evidence suggests it may be a culture-bound construct. Almost 50% of American women crave chocolate specifically around the onset of menstruation. Research does not support popular accounts implicating physiological factors in menstrual chocolate craving etiology. We tested the novel hypothesis that greater menstrual craving prevalence in the U.S. is the product of internalized cultural norms. Women of diverse backgrounds (n = 275) reported on craving frequency and triggers and completed validated measures of acculturation. Foreign-born women were significantly less likely to endorse menstrual chocolate craving (17.3%), compared to women born to U.S.-born parents (32.7%, p = .03) and second generation immigrants (40.9%, p = .001). Second generation immigrant and foreign-born women endorsing menstrual chocolate craving reported significantly greater U.S. acculturation and lower identification with their native culture than non-menstrual cravers (all p < .001). Findings inform our understanding of food cravings, with important implications for the study of cravings in other domains.
| S-EPMC5517000 | biostudies-literature
Project description:ObjectivesWhen examining the relationship between smoking intensity and toxicant exposure biomarkers in an effort to understand the potential risk for smoking-related disease, individual biomarkers may not be strongly associated with smoking intensity because of the inherent variability in biomarkers. Structural equation modeling (SEM) offers a powerful solution by modeling the relationship between smoking intensity and multiple biomarkers through a latent variable.MethodsBaseline data from a randomized trial (N = 1250) were used to estimate the relationship between smoking intensity and a latent toxicant exposure variable summarizing five volatile organic compound biomarkers. Two variables of smoking intensity were analyzed: the self-report cigarettes smoked per day and total nicotine equivalents in urine. SEM was compared with linear regression with each biomarker analyzed individually or with the sum score of the five biomarkers.ResultsSEM models showed strong relationships between smoking intensity and the latent toxicant exposure variable, and the relationship was stronger than its counterparts in linear regression with each biomarker analyzed separately or with the sum score.ConclusionsSEM is a powerful multivariate statistical method for studying multiple biomarkers assessing the same class of harmful constituents. This method could be used to evaluate exposure from different combusted tobacco products.
| S-EPMC9075702 | biostudies-literature
Project description:IntroductionGlobal evidence suggests that natural disasters are on the rise, and that earthquake harm disproportionally impacts developing countries. To mitigate these harms, disaster preparedness is an important behavioral strategy in earthquake risk mitigation. However, there is limited evidence about the levels of preparedness in developing countries, especially Iran. Therefore, this study aimed to investigate earthquake preparedness among the general public, using the Theory of Planned Behavior (TPB) as a theoretical framework.MethodThis methodological study was conducted in Iran in 2022, involving 302 participants selected through stratified random sampling. Data was collected using a valid and reliable questionnaire. Structural equation modeling (SEM) was employed to analyze TPB constructs, including attitudes, subjective norms, perceived behavioral control, and intentions, in relation to earthquake preparedness behaviors. The statistical analyses encompassed descriptive statistics, t-tests, ANOVA, correlation coefficients, confirmatory factor analysis, and structural equation modeling.ResultsResults show that attitudes toward disaster preparedness, subjective norms, and perceived behavioral control significantly (< 0.05) influenced residents' disaster preparedness intentions. Additionally, there was good model fit of the TPB in explaining earthquake preparedness behavior. For confirmatory factor analysis (CFA) of TPB model the fit indices were CMin/df = 1.35 (< 3), RMSEA = 0.03 (< 0.05); CFI = 0.96 (> 0.95); TLI = 0.95 (= 0.95), and for SEM model they were CMin/df = 1.36 (< 3), RMSEA = 0.03 (< 0.05); CFI = 0.96 (> 0.95); TLI = 0.96 (> 0.95).ConclusionThe overall fit indexes were acceptable indicating the TPB model is a valid and reliable measurement model for screening population-level readiness for earthquake preparedness, developing and/or implementing health promotion interventions. The findings also suggest that disaster education programs should emphasize the importance of attitudes, subjective norms, and perceived behavioral control in promoting disaster preparedness.
| S-EPMC11792548 | biostudies-literature