This study aimed to identify meal and snack patterns and assess their association with sleep timing in schoolchildren. This is a cross-sectional study carried out in 2018/2019 with 1333 schoolchildren aged 7–14 years from public and private schools in Florianópolis, Brazil. Previous-day dietary intake data for breakfast, mid-morning snack, lunch, mid-afternoon snack, dinner, and evening snack were collected using a validated online questionnaire. Sleep timing was measured by the midpoint of sleep and classified as quartiles (very early, early, late and very late). Latent Class Analysis was performed to identify meal and snack patterns, and multinomial logistic regression was used to assess associations. Students with very late sleep timing were less likely to consume the “Coffee with milk, bread and cheese” breakfast pattern compared with very early group (35.4%, 95%CI 27.2-43.6 vs. 56.0%, 95%CI 48.5-63.4). Also, the former were more likely to consume the “Mixed” breakfast pattern (healthy and unhealthy foods) compared with very early students (40.0%, 95%CI 32.4- 46.7 vs. 28.0%, 95%CI 23.8- 32.0). The latter were more likely to eat the “Brazilian traditional, processed meat, egg and fish” lunch pattern to the late students (35.4%, 95%CI 30.3- 40.5 vs. 21.5%, 95%CI 15.2- 27.8) and less likely to consume the “Pasta and cheese” lunch pattern compared to the students with later sleep timing (10.1%, 95%CI 8.4- 11.9 vs. 17.1%, 95%CI 13.0- 21.1). Students with later sleep timing were more likely to eat ultra-processed food at mid-afternoon snacks compared with early group (56.3%, 95%CI 52.4- 60.2 vs. 47.2%, 95%CI 43.5- 50.8). The study findings suggest that morning preference appears to promote healthier breakfast, lunch, and afternoon snack patterns, whereas later sleep timing may pose challenges in maintaining healthy patterns at these meals/snacks.

This paper investigates the market position of hard cider within the broader alcoholic beverage market. The first experiment identifies two distinct consumer segments—around 40% prioritize flavor attributes, while 53% prefer production information. The second experiment utilizes a basket- and expenditure-based choice experiment and a multiple discrete choice extreme value model to assess hard cider's standing among commonly consumed alcoholic beverages. Results reveal that hard cider is perceived as a complement to red and white wine but is independent from beer. The study suggests marketing hard cider in conjunction with white wine to capitalize on observed complementarity. Emphasizing the importance of addressing both consumer segments—those valuing flavor notes and those prioritizing production information—the research offers valuable insights for optimizing hard cider market strategies.

Integrating farmers’ preferences into the breeding and dissemination of new genotypes is a effective approach to enhance their successful adoption by farmers. In the case of sweet potato, a staple crop in many parts of West Africa, there is a need for more research on the selection criteria used by farmers when choosing which varieties to grow. This study aims to highlight farmers’ selection criteria for sweet potato varieties in the main production areas in Benin. A total of 480 farmers from the top three sweet potato production areas were surveyed. The relative importance of various traits for sweet potato farmers was evaluated using best-worst scaling methods. Latent class analysis was applied to find groups of farmers with similar preferences. Best-Worst Scaling analysis revealed that high root yield, root size, marketability, and early maturing were the most important variety selection criteria. Latent class analysis revealed three farmers’ groups referred to as ‘Yield potential’, ‘Market value’, and ‘Plant resilience’ classes. ‘Yield potential’ farmers were more likely to be from Atlantique and Alibori departments; they significantly committed more acreage to sweet potato production. The ‘Market value’ farmers highlighted the variety of root size and commercial value as the main selection criteria and consisted of farmers with primary education levels from the Ouémé department. ‘Plant resilience’ refers to a group of Alibori farmers who prioritize environmental issues and primarily grow sweet potatoes for self-consumption. Our findings shed light on farmers’ preferences and suggested that heterogeneity in sweet potato selection criteria was highly influenced by various socio-economic factors and location.

Understanding farmers’ preferences and willingness to pay for different traits is critical for demand-driven varietal development and designing targeted strategies that stimulate adoption of varieties by farmers. This study uses choice experiment data from a random sample of 1299 Tanzanian farmers to analyze their preferences for traits of groundnut varieties, investigate trade-offs involved in valuation of attributes, and explore heterogeneity in preferences. Results reveal that farmers have strong preferences for groundnut varieties that are high yielding, tolerant to environmental stresses, early-maturing, red-colored, and fetching high sale prices in grain markets. Farmers are willing to pay the highest premium for high-yielding attributes, closely followed by the tolerance trait. Further, a latent class analysis identifies four distinct classes of farmers, confirming considerable heterogeneity in farmers’ preferences for various groundnut traits. A specific distinction is notable between preferences of consumption-oriented and market-oriented farmer classes. Our results have important implications for demand-driven variety development and targeted dissemination of improved varieties.

Conduct problems and head injuries increase the risk of delinquency and share a bidirectional association. However, how they link across development is unknown. The present study aimed to identify their linked developmental pathways and associated risk factors. Latent class analysis was modeled from Millennium Cohort Study data (n = 8,600) to identify linked pathways of conduct problem symptoms and head injuries. Head injuries were parent-reported from ages 3 to 14 and conduct problems from ages 3 to 17 using the Strengths and Difficulties Questionnaire (SDQ). Multinomial logistic regression then identified various risk factors associated with pathway membership. Four distinct pathways were identified. Most participants displayed low-level conduct problem symptoms and head injuries (n = 6,422; 74.7%). Three groups were characterized by clinically relevant levels of conduct problem symptoms and high-risk head injuries in childhood (n = 1,422; 16.5%), adolescence (n = 567; 6.6%), or persistent across development (n = 189; 2.2%). These clinically relevant pathways were associated with negative maternal parenting styles. These findings demonstrate how pathways of conduct problem symptoms are uniquely linked with distinct head injury pathways. Suggestions for general preventative intervention targets include early maternal negative parenting styles. Pathway-specific interventions are also required targeting cumulative risk at different ecological levels.

We apply a multisystem perspective to three aims relevant to resilience for young children in emergency and transitional homeless shelters. We consider profiles of risks and resources before shelter, early childhood program enrollment during shelter, and the likelihood of returning to shelter or having a subsequent child welfare placement. We used longitudinal, city-wide data from multiple sources integrated at the individual level across the lifespan for 8 birth cohorts. Young children (N = 1,281) stayed in family shelters during an 18-month period during a multisystem intervention. Risk factor rates were high as were rates of early childhood program enrollment (66.1% in any program; 42.3% in a high-quality program), which may suggest positive effects of the multisystem intervention. Multilevel latent class analysis revealed four profiles, considering prior shelter stays, prior child welfare placements, prior elevated lead levels, perinatal factors (teenage mother, prenatal care, low maternal education, and poor birth outcomes), demographics, and early childhood program enrollment and quality. One profile with higher rates of child welfare placement before the shelter stay and considerable enrollment in high-quality early childhood programs corresponded to lower rates of subsequent child welfare placement. Profiles did not differ on the likelihood of returning to shelter.

We aimed to identify temporal patterns of energy intake and investigate their association with adiposity. We performed a cross-sectional study of 775 adults in Iran. Information about eating occasions across the day was collected by three 24-h dietary recalls. Latent class analysis (LCA) was used to identify temporal eating patterns based on whether or not an eating occasion occurred within each hour of the day. We applied binary logistic regression to estimate the OR and 95 % CI of overweight and obesity (defined as BMI of 25–29·9 and ≥ 30 kg/m2, respectively) across temporal eating patterns while controlling for potential confounders. LCA grouped participants into three exclusive sub-groups named ‘Conventional’, ‘Earlier breakfast’ and ‘Later lunch’. The ‘Conventional’ class was characterised by high probability of eating occasions at conventional meal times. ‘Earlier breakfast’ class was characterised by high probability of a breakfast eating occasion 1 h before the conventional pattern and a dinner eating occasion 1 h after the conventional pattern, and the ‘Later lunch’ class was characterised by a high probability of a lunch eating occasion 1 h after the conventional pattern. Participants in the ‘Earlier breakfast’ pattern had a lower likelihood of obesity (adjusted OR: 0·56, 95 % CI: 0·35, 0·95) as compared with the ‘Conventional’ pattern. There was no difference in the prevalence of obesity or overweight between participants in the ‘Later lunch’ and the ‘Conventional’ patterns. We found an inverse association between earlier eating pattern and the likelihood of obesity, but reverse causation may be a plausible explanation.

The characteristics of Australian retirement village residents, an under-researched population, are not well understood. Knowledge of their wellbeing and modifiable factors associated with low wellbeing would aid in the introduction of health promotion measures and supports to facilitate healthy ageing-in-place. A novel approach utilising latent class analysis (LCA), a statistical method not previously employed to study this population, was undertaken to analyse cross-sectional survey data from 871 participants aged ≥65 years from retirement villages in Queensland, Australia. LCA identified latent, i.e. unobserved, underlying and often difficult to measure, groups within this population based on the responses of individuals to multiple observed variables. Survey participants were divided into groups, each with a distinct profile associated with a wellbeing state, as determined by responses to questions about physical health, unplanned hospitalisations, cognitive health and social connectedness. Multinomial logistic regression explored the relationship between modifiable health and lifestyle characteristics and membership of a particular wellbeing group. The median age of participants was 82 years (interquartile range = 76–88). While 69.0 per cent reported good to excellent health, polypharmacy was evident with 45.6 per cent of participants taking five or more prescription medications. In the previous 12 months, 33.3 per cent had experienced one or more falls and 30.6 per cent an unplanned hospitalisation. Distinct profiles were identified for three wellbeing groups: high (57.7% of participants), moderate (20.6%) and low wellbeing (21.7%). Injurious falls, limited ability to prepare meals and debilitating pain were associated with the moderate and low wellbeing groups. Physical activity significantly lowered the probability of a retirement village resident being in the low wellbeing group. Our findings highlight falls prevention, maintaining adequate nutrition, pain management and regular physical activity as actions that may optimise wellbeing, mitigate functional decline and support the independence of retirement village residents into later years of life.

The present study aimed to (1) examine the changes in sleep habits and dietary intake among school-aged children after the school re-opening from a 3-month closure (without school lunch) due to the COVID-19 pandemic, and (2) examine whether the changes differ between those with different temporal patterns of sleep and eating during school closure, namely, ‘Very early’, ‘Early’, ‘Late’ and ‘Very late’. The latter patterns were characterised by later timings of wake up, breakfast and lunch. Questionnaires were answered twice by 4084 children (aged 8–15 years), themselves and/or their parents: first in June 2020 (for assessing lifestyle during school closure) and second, from July 2020 to February 2021 (for assessing lifestyle after school opening). After school re-opening, the participants’ wake-up time became an hour earlier (95 % CI 1⋅0, 1⋅1) and sleep duration got 0⋅94 h shorter (95 % CI 0⋅91, 0⋅97) than during school closure. An increase in dietary intake was observed for thiamine, vitamin B6, potassium, fruits and dairy products, and a decrease was observed for sugars (as foods) and confectioneries and sweetened beverages, despite small effect sizes (Cohen's d: 0⋅20–0⋅30). Significant changes in wake-up time, sleep duration and sweetened beverage intake were observed among children with the latter temporal patterns. Thus, children wake up earlier and sleep for shorter durations after school re-opening than during school closure; however, changes in dietary intake were generally insignificant. Dietary intake among school-aged children in Japan during school closure (without school lunch) might not be worse than that during school days with universal school lunch.

Early adolescents (ages 10–14) living in low- and middle-income countries have heightened vulnerability to psychosocial risks, but available evidence from these settings is limited. This study used data from the Global Early Adolescent Study to characterize prototypical patterns of emotional and behavioral problems among 10,437 early adolescents (51% female) living in the Democratic Republic of Congo (DRC), Malawi, Indonesia, and China, and explore the extent to which these patterns varied by country and sex. LCA was used to identify and classify patterns of emotional and behavioral problems separately by country. Within each country, measurement invariance by sex was evaluated. LCA supported a four-class solution in DRC, Malawi, and Indonesia, and a three-class solution in China. Across countries, early adolescents fell into the following subgroups: Well-Adjusted (40–62%), Emotional Problems (14–29%), Behavioral Problems (15–22%; not present in China), and Maladjusted (4–15%). Despite the consistency of these patterns, there were notable contextual differences. Further, tests of measurement invariance indicated that the prevalence and nature of these classes differed by sex. Findings can be used to support the tailoring of interventions targeting psychosocial adjustment, and suggest that such programs may have utility across diverse cross-national settings.

Few studies have utilized person-centered approaches to examine co-occurrence of risk factors among pregnant women in low-and middle-income settings. The objective of this study was to utilize latent class analysis (LCA) to identify sociodemographic patterns and assess the association of these patterns on preterm birth (PTB) and/or low birth weight (LBW) in rural Mysore District, India. Secondary data analysis of a prospective cohort study among 1540 pregnant women was conducted. Latent class analysis was performed to identify distinct group memberships based on a chosen set of sociodemographic factors. Binary logistic regression was conducted to estimate the association between latent classes and preterm birth and low birth weight. LCA yielded four latent classes. Women belonging to Class 1 “low socioeconomic status (SES)/early marriage/multigravida/1 child or more”, had higher odds of preterm birth (adjusted Odds Ratio (aOR): 95% Confidence Intervals (CI): 1.77, 95% CI: 1.05-2.97) compared to women in Class 4 “high SES/later marriage/primigravida/no children”. Women in Class 2 “low SES/later marriage/primigravida/no children” had higher odds of low birth weight (aOR: 2.52, 95% CI: 1.51-4.22) compared to women in Class 4. Women less than 20 years old were twice as likely to have PTB compared to women aged 25 years and older (aOR: 2.00, 95% CI: 1.08-3.71). Hypertension (>140/>90 mm/Hg) was a significant determinant of PTB (aOR: 2.28, 95% CI: 1.02-5.07). Furthermore, women with a previous LBW infant had higher odds of delivering a subsequent LBW infant (aOR: 2.15, 95% CI: 1.40-3.29). Overall study findings highlighted that woman belonging to low socioeconomic status, and multigravida women had increased odds of preterm birth and low birth weight infants. Targeted government programs are crucial in reducing inequalities in preterm births and low birth weight infants in rural Mysore, India.

Current conceptualizations of oppositional defiant disorder (ODD) place the symptoms of this disorder within three separate but related dimensions (i.e., angry/irritable mood, argumentative/defiant behavior, vindictiveness). Variable-centered models of these dimensions have yielded discrepant findings, limiting their clinical utility. The current study utilized person-centered latent class analysis based on self and parent report of ODD symptomatology from a community-based cohort study of 521 adolescents. We tested for sex, race, and age differences in the identified classes and investigated their ability to predict later symptoms of depression and conduct disorder (CD). Diagnostic information regarding ODD, depression, and CD were collected annually from adolescents (grades 6–9; 51.9% male; 48.7% White, 28.2% Black, 18.5% Asian) and a parent. Results provided evidence for three classes of ODD (high, medium, and low endorsement of symptoms), which demonstrated important developmental differences across time. Based on self-report, Black adolescents were more likely to be in the high and medium classes, while according to parent report, White adolescents were more likely to be in the high and medium classes. Membership in the high and medium classes predicted later increases in symptoms of depression and CD, with the high class showing the greatest risk for later psychopathology.

In many parts of the world, older adults continue to face significant barriers to digital inclusion, but the source of that inequality is not well understood. However, we do not know enough about differences among older people seeking to improve their digital skills. Examining the impact of a national three-year digital inclusion programme reaching more than 580,000 older adults in Australia, this study explores factors that affect digital skills and literacy later in life. A mixed-methods approach involving a two time-point survey (N = 337) along with participant interviews (N = 30) examined the effectiveness of programme elements. A latent class analysis was applied to examine differences in the way older adults engage with digital technologies. Qualitative analysis helped to detail those differences. Programme outcomes were far from uniform, reflecting diverse motivations, lifecourse experiences, needs and capabilities among older adults, countering much existing research that tends to elide those differences. With reference to the concept of situated literacies, we highlight the importance of life experiences, needs and motivations to the outcomes of digital inclusion interventions. Our findings emphasise the need to disaggregate older adult internet users, and account for differences in life experiences, needs and motivations in the design and delivery of digital inclusion interventions at scale.