Diet is a major lifestyle-related risk factor of various chronic diseases. Dietary intake can be assessed by subjective report and objective observation. Subjective assessment is possible using open-ended surveys such as dietary recalls or records, or using closed-ended surveys including food frequency questionnaires. Each method has inherent strengths and limitations. Continued efforts to improve the accuracy of dietary intake assessment and enhance its feasibility in epidemiological studies have been made. This article reviews common dietary assessment methods and their feasibility in epidemiological studies.

There is growing evidence for a global transition to a more highly processed diet. While the dietary share of ultra-processed foods depends on a country’s economic status, food choice and consumption are also influenced by the socioeconomic situation of individuals. This study investigated whether ultra-processed food consumption differed across socioeconomic subgroups and over time (2010–2018) in Korea. Cross-sectional data from the Korea National Health and Nutrition Examination Survey 2010–2018 were analyzed. Food and beverages reported in a one-day 24 h recall were classified according to the NOVA food classification criteria. The dietary energy contribution of ultra-processed foods was high among men and urban residents, and increased with education and income level; additionally, it reached its peak in adolescents and thereafter decreased with increasing age. After adjusting the socioeconomic variables, such associations remained significant, except for income level. The overall contribution of ultra-processed foods increased from 23.1% (2010–2012) to 26.1% (2016–2018), and the same trend over time was observed in all age groups and socioeconomic strata. In the Korean population, ultra-processed food consumption differed by individual socioeconomic characteristics, but gradually increased over time, and this trend was consistently found in all socioeconomic subgroups. Future strategies to promote healthy food choices are needed for the Korean population.

Food environments have changed rapidly, and the global interest in ultra-processed foods has increased. Ultra-processed foods are typically energy dense, high in sugars and fat, and low in fiber, protein, minerals, and vitamins. This study aimed to estimate the energy contribution of ultra-processed foods in the diet of Korean adults and to examine the association between ultra-processed food consumption and dietary intake and diet quality. This study is a secondary analysis of cross-sectional data from the Korea National Health and Nutrition Examination Survey (2016-2018). A total of 16,657 adults aged ≥19 years who completed a 1-day 24-hour recall. Absolute and relative intake of energy and nutrients were measured and dietary quality was assessed using the Korean Healthy Eating Index (KHEI). Multiple regression models adjusted for sociodemographic variables were used to examine the association between quintiles of ultra-processed foods dietary energy contribution and dietary intake and quality. Mean reported daily energy intake was 2,031 kcal, with 25.1% of calories coming from ultra-processed foods. Mean energy contribution from ultra-processed foods ranged from 3.6% kcal (Q1) to 52.4% kcal (Q5). Energy contribution of ultra-processed foods was positively associated with reported intake of daily energy, total sugars, and total and saturated fat and inversely associated with reported intake of carbohydrates, fiber, minerals, and vitamins. Both sodium and potassium were negatively associated with percentage of energy from ultra-processed foods. However, the sodium-to-potassium ratio was high regardless of quintile of energy contribution from ultra-processed foods, and the ratio was positively associated with percentage of total energy from ultra-processed foods. Although the KHEI score was inversely associated with percentage of daily energy from ultra-processed foods, all levels of ultra-processed food consumption were associated with poor diet quality. The ultra-processed foods consumption of Korean adults accounted for one fourth of daily energy intake, and a higher dietary energy contribution from ultra-processed foods was associated with poorer dietary intakes and a lower dietary quality. Further studies are needed to understand factors influencing selection and consumption of ultra-processed foods and to identify effective strategies to promote healthy food choices.

Background: This study aimed to investigate the prevalence and status of dyslipidemia management among South Korean adults, as performed by the Korean Society of Lipid and Atherosclerosis under the name Dyslipidemia Fact Sheet 2022.Methods: We analyzed the lipid profiles, age-standardized and crude prevalence, management status of hypercholesterolemia and dyslipidemia, and health behaviors among Korean adults aged ≥20 years, using the Korea National Health and Nutrition Examination Survey data between 2007 and 2020.Results: In South Korea, the crude prevalence of hypercholesterolemia (total cholesterol ≥240 mg/dL or use of a lipid-lowering drug) in 2020 was 24%, and the age-standardized prevalence of hypercholesterolemia more than doubled from 2007 to 2020. The crude treatment rate was 55.2%, and the control rate was 47.7%. The crude prevalence of dyslipidemia—more than one out of three conditions (low-density lipoprotein cholesterol ≥160 or the use of a lipid-lowering drug, triglycerides ≥200, or high-density lipoprotein cholesterol [HDL-C] [men and women] <40 mg/dL)—was 40.2% between 2016 and 2020. However, it increased to 48.2% when the definition of hypo-HDL-cholesterolemia in women changed from <40 to <50 mg/dL.Conclusion: Although the prevalence of hypercholesterolemia and dyslipidemia has steadily increased in South Korea, the treatment rate remains low. Therefore, continuous efforts are needed to manage dyslipidemia through cooperation between the national healthcare system, patients, and healthcare providers.

Background: Dyslipidemia is a multifactorial disorder, which arises from complex interactions among genetic and environmental risk factors. Previous studies have established the deteriorating effect of aging on lipid profiles. However, little is known about the role of education level, a stable marker of socioeconomic status, which reflect modifiability of lifestyle risk factors. Therefore, we examined the association between age and individual dyslipidemia parameter across education level among healthy, middle-aged Korean women. Methods: From 2049 middle-aged women, education attainment was classified into completion of elementary school or below, middle school, high school, college or above. Dyslipidemia was assessed in adherence to the 2018 Korean Dyslipidemia Treatment Guideline. Multivariable logistic regression and generalized linear model tested for associations between age and dyslipidemia parameter across education level and other known risk factors, including menopause, obesity, and current drinking and smoking. Results: In this cross-sectional analysis, the prevalence of each dyslipidemia parameter was significantly different by age and education level. The odds ratio (OR) for dyslipidemia was higher among participants who were older and had received higher education (OR = 2.31, p for interaction = 0.008) than younger and low education counterpart. The interaction between age and education level remained significant for hypercholesterolemia (p for interaction = 0.003) and hyper-LDL-cholesterolemia (p for interaction = 0.002). Conclusions: Separate examination of individual dyslipidemia parameter indicated varying degree of interaction with age and education level. Such results imply that each type of lipid abnormality may arise from and be exacerbated by heterogeneous composition of biological and lifestyle risk factors, which may be reflected by education level.

Background: Metabolic disorders are established precursors to cardiovascular diseases, yet they can be readily prevented with sustained lifestyle modifications. Objective: We assessed the effectiveness of a smartphone-based weight management app on metabolic parameters in adults at high-risk, yet without physician diagnosis nor pharmacological treatment for metabolic syndrome, in a community setting. Methods: In this 3-arm parallel-group, single-blind, randomized controlled trial, we recruited participants aged 30 to 59 years with at least 2 conditions defined by the Third Report of the National Cholesterol Education Program expert panel (abdominal obesity, high blood pressure, high triglycerides, low high-density lipoprotein cholesterol, and high fasting glucose level). Participants were randomly assigned (1:1:1) by block randomization to either the nonuser group (control), the app-based diet and exercise self-logging group (app only), or the app-based self-logging and personalized coaching from professional dieticians and exercise coordinators group (app with personalized coaching). Assessments were performed at baseline, week 6, week 12, and week 24. The primary outcome was change in systolic blood pressure (between baseline and follow-up assessments). Secondary outcomes were changes in diastolic blood pressure, body weight, body fat mass, waist circumference, homeostatic model of assessment of insulin resistance, triglyceride level, and high-density lipoprotein cholesterol level between baseline and follow-up assessments. Analysis was performed using intention-to-treat. Results: Between October 28, 2017 and May 28, 2018, 160 participants participated in the baseline screening examination. Participants (129/160, 80.6%) who satisfied the eligibility criteria were assigned to control (n=41), app only (n=45), or app with personalized coaching (n=43) group. In each group, systolic blood pressure showed decreasing trends from baseline (control: mean –10.95, SD 2.09 mmHg; app only: mean –7.29, SD 1.83 mmHg; app with personalized coaching: mean –7.19, SD 1.66 mmHg), yet without significant difference among the groups (app only: P=.19; app with personalized coaching: P=.16). Instead, those in the app with personalized coaching group had greater body weight reductions (control: mean –0.12, SD 0.30 kg; app only: mean –0.35, SD 0.36 kg, P=.67; app with personalized coaching: mean –0.96, SD 0.37 kg; P=.08), specifically by body fat mass reduction (control: mean –0.13, SD 0.34 kg; app only: mean –0.64, SD 0.38 kg, P=.22; app with personalized coaching: mean –0.79, SD 0.38 kg; P=.08). Conclusions: Simultaneous diet and exercise self-logging and persistent lifestyle modification coaching were ineffective in lowering systolic blood pressure but effective in losing weight and reducing body fat mass. These results warrant future implementation studies of similar models of care on a broader scale in the context of primary prevention. Trial Registration: ClinicalTrials.gov NCT03300271; http://clinicaltrials.gov/ct2/show/NCT03300271