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BACKGROUND: It is unknown whether dietary intake of polyunsaturated fatty acids (PUFA) modifies the cardiovascular disease (CVD) risk associated with a family history of CVD. We assessed interactions between biomarkers of low PUFA intake and a family history in relation to long-term CVD risk in a large consortium. METHODS: Blood and tissue PUFA data from 40 885 CVD-free adults were assessed. PUFA levels ≤25th percentile were considered to reflect low intake of linoleic, alpha-linolenic, and eicosapentaenoic/docosahexaenoic acids (EPA/DHA). Family history was defined as having ≥1 first-degree relative who experienced a CVD event. Relative risks with 95% CI of CVD were estimated using Cox regression and meta-analyzed. Interactions were assessed by analyzing product terms and calculating relative excess risk due to interaction. RESULTS: After multivariable adjustments, a significant interaction between low EPA/DHA and family history was observed (product term pooled RR, 1.09 [95% CI, 1.02-1.16]; P=0.01). The pooled relative risk of CVD associated with the combined exposure to low EPA/DHA, and family history was 1.41 (95% CI, 1.30-1.54), whereas it was 1.25 (95% CI, 1.16-1.33) for family history alone and 1.06 (95% CI, 0.98-1.14) for EPA/DHA alone, compared with those with neither exposure. The relative excess risk due to interaction results indicated no interactions. CONCLUSIONS: A significant interaction between biomarkers of low EPA/DHA intake, but not the other PUFA, and a family history was observed. This novel finding might suggest a need to emphasize the benefit of consuming oily fish for individuals with a family history of CVD.

ObjectiveInitiatives to reduce neighborhood-based health disparities require access to meaningful, timely, and local information regarding health behavior and its determinants. We examined the validity of Twitter as a source of information for neighborhood-level analysis of dietary choices and attitudes.Materials and methodsWe analyzed the "healthiness" quotient and sentiment in food-related tweets at the census tract level, and associated them with neighborhood characteristics and health outcomes. We analyzed keywords driving the differences in food healthiness between the most and least-affluent tracts, and qualitatively analyzed contents of a random sample of tweets.ResultsSignificant, albeit weak, correlations existed between healthiness and sentiment in food-related tweets and tract-level measures of affluence, disadvantage, race, age, U.S. density, and mortality from conditions associated with obesity. Analyses of keywords driving the differences in food healthiness revealed foods high in saturated fat (eg, pizza, bacon, fries) were mentioned more frequently in less-affluent tracts. Food-related discussion referred to activities (eating, drinking, cooking), locations where food was consumed, and positive (affection, cravings, enjoyment) and negative attitudes (dislike, personal struggles, complaints).DiscussionTweet-based healthiness scores largely correlated with offline phenomena in the expected directions. Social media offer less resource-intensive data collection methods than traditional surveys do. Twitter may assist in informing local health programs that focus on drivers of food consumption and could inform interventions focused on attitudes and the food environment.ConclusionsTwitter provided weak but significant signals concerning food-related behavior and attitudes at the neighborhood level, suggesting its potential usefulness for informing local health disparity reduction efforts.

Objectives: This study aimed to assess malnutrition and muscle mass depletion risk in gastrointestinal cancer patients, exploring the differences between gastric and colorectal cancer, with a focus on gender0specific variations and dietary intake. It also examined whether muscle depletion mediates the relationship between dietary intake and malnutrition risk. Methods: A sample of 100 Jordanian pre-operative gastrointestinal cancer patients (60 male, 40 female) with gastric or colorectal cancer were assessed for malnutrition risk using the malnutrition universal screening tool (MUST) and for muscle depletion using fat-free mass index (FFMI) and mid-upper arm muscle area (MUAMA). Results: The study found that 80% (95% CI: 0.708–0.873) of patients were at high risk of malnutrition, with over 60% experiencing severe muscle loss. Gastric cancer patients showed higher, though not statistically significant, malnutrition risk (90.2% vs. 72.9%) and muscle depletion compared to colorectal cancer patients. Advanced cancer stages were associated with significantly higher risk of malnutrition and muscle depletion. Significant gender-specific differences in muscle depletion via FFMI (p = 0.012) and via MUAMA (p = 0.028) were also noted, especially in females with gastric cancer. Additionally, males exhibited a significantly higher malnutrition risk (p < 0.001) based on cancer stage. Patients' dietary intake was significantly (p < 0.001) below the recommended levels for energy, protein, carbohydrates, fiber, and essential fatty acids, which was associated with higher malnutrition risk, muscle depletion, low BMI (<18.5 kg/m2), and significant weight loss (>10%). Low dietary intake was strongly linked to increased malnutrition risk and muscle depletion, with muscle loss partially mediating (b = 0.4972, p < 0.0001) the relationship between poor dietary intake and malnutrition risk. Additionally, higher muscle mass was protective against malnutrition (OR = 16.0, 95% CI: 1.706–150.507), and cancer type was a significant predictor of malnutrition risk (OR = 14.4, 95% CI: 1.583–130.867). Conclusions: Malnutrition risk and significant muscle loss are common in GI cancer patients, highlighting the urgent need for tailored nutrition care plans and lifestyle modifications. [ABSTRACT FROM AUTHOR]

Risk factors can drive socioeconomic inequalities in cardiovascular disease (CVD) through differential exposure and differential vulnerability. In this paper, we show how econometric decomposition directly enables simultaneous, policy-oriented assessment of these 2 mechanisms. We specifically estimate contributions of neighborhood environment and proximal risk factors to socioeconomic inequality in CVD incidence via these mechanisms. We followed 5,608 participants in the Multi-Ethnic Study of Atherosclerosis (2000-2012) to their first CVD event (median length of follow-up, 12.2 years). We used a summary measure of baseline socioeconomic position (SEP). Covariates included baseline demographics, neighborhood characteristics, and psychosocial, behavioral, and biomedical risk factors. Using Poisson models, we decomposed the difference (inequality) in incidence rates between low- and high-SEP groups into contributions of 1) differences in covariate means (differential exposure) and 2) differences in CVD risk associated with covariates (differential vulnerability). Notwithstanding large uncertainty in neighborhood estimates, our analysis suggested that differential exposure to poorer neighborhood socioeconomic conditions, adverse social environment, diabetes, and hypertension accounted for most of the inequality. Psychosocial and behavioral contributions were negligible. Further, neighborhood SEP, female sex, and white race were more strongly associated with CVD among low-SEP (vs. high-SEP) participants. These differentials in vulnerability also accounted for nontrivial portions of the inequality and could have important implications for intervention.

Abstract Background The interactive effects of different types of physical activity on cardiovascular disease (CVD) risk have not been fully considered in previous studies. We aimed to identify physical activity patterns that take into account combinations of physical activities and examine the association between derived physical activity patterns and risk of acute myocardial infarction (AMI). Methods We examined the relationship between physical activity patterns, identified by principal component analysis (PCA), and AMI risk in a case-control study of myocardial infarction in Costa Rica (N=4172), 1994-2004. The component scores derived from PCA and total METS were used in natural cubic spline models to assess the association between physical activity and AMI risk. Results Four physical activity patterns were retained from PCA that were characterized as the rest/sleep, agricultural job, light indoor activity, and manual labor job patterns. The light indoor activity and rest/sleep patterns showed an inverse linear relation (P for linearity=0.001) and a U-shaped association (P for non-linearity=0.03) with AMI risk, respectively. There was an inverse association between total activity-related energy expenditure and AMI risk but it reached a plateau at high levels of physical activity (P for non-linearity=0.01). Conclusions These data suggest that a light indoor activity pattern is associated with reduced AMI risk. PCA provides a new approach to investigate the relationship between physical activity and CVD risk.

Adopting sustainable dietary patterns is essential for planetary and human health. As data to address this issue are lacking in Latino populations, this study examined the association between diet-attributable greenhouse gas emissions (GHGEs) and myocardial infarction (MI) in a Costa Rica Heart Study. This analysis included 1817 cases of a first non-fatal acute MI during hospitalization and their matched population-based controls, by age, sex, and area of residence. A validated food frequency questionnaire was used to quantify habitual dietary intake and diet-attributable GHGEs (kg CO2 equivalent (eq.)/year). Due to the matching design, conditional logistic regression was used. Red meat consumption contributed approximately 50% to the total diet-attributable GHGEs among both cases and controls. Higher diet-attributable GHGEs were associated with increased odds of acute MI. The odds of MI were 63% higher (OR = 1.63; 95% CI 1.20–2.21) among participants in the highest quintile (median diet-attributable GHGEs = 6247 kg CO2 eq./year) compared to the lowest quintile (median diet-attributable GHGEs = 2065 kg CO2 eq./year). An increasing linear trend in the odds of acute MI and diet-attributable GHGEs was detected (p-trend 0.0012). These findings highlight the importance of reducing red meat consumption to sustainably mitigate the incidence of MI and improve planetary health. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the associations between household food insecurity and diabetes risk factors among lower-income US adolescents. Design: Cross-sectional analysis. Household food security status was measured using the 18-item Food Security Survey Module. Simple and multivariable linear and logistic regressions were used to assess the association between food security status and fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), HbA1C and homoeostatic model assessment – insulin resistance (HOMA-IR). The analyses were adjusted for household and adolescent demographic and health characteristics. Setting: USA. Participants: 3412 US adolescents aged 12–19 years with household incomes ≤300 % of the federal poverty line from the National Health and Nutrition Examination Survey cycles 2007–2016. Results: The weighted prevalence of marginal food security was 15·4 % and of food insecurity was 32·9 %. After multivariate adjustment, adolescents with food insecurity had a 0·04 % higher HbA1C (95 % CI 0·00, 0·09, P -value = 0·04) than adolescents with food security. There was also a significant overall trend between severity of food insecurity and higher HbA1C (P trend = 0·045). There were no significant mean differences in adolescents' FPG, OGTT or HOMA-IR by household food security. Conclusions: Food insecurity was associated with slightly higher HbA1c in a 10-year sample of lower-income US adolescents aged 12–19 years; however, other associations with diabetes risk factors were not significant. Overall, this suggests slight evidence for an association between food insecurity and diabetes risk in US adolescents. Further investigation is warranted to examine this association over time. [ABSTRACT FROM AUTHOR]