The study analysed data from the nationally representative Daily Life Aspects cross-sectional surveys conducted in Italy from 2015 through 2022. Its population comprised 84,797 participants aged 0–29: 77,097 with both parents holding Italian citizenship and 7,700 with at least one foreign-citizen parent. The researchers used multivariable logistic regression models with household-clustered standard errors to estimate adjusted odds ratios for six outcomes: non-good self-rated health, overweight or obesity, sedentary lifestyle, low fruit and vegetable consumption, at-risk alcohol use and smoking. The models adjusted for demographic, socioeconomic, household and contextual factors.

After adjustment, participants with at least one foreign-citizen parent had 15% higher odds of overweight or obesity, with an adjusted odds ratio of 1.15 and a 95% confidence interval of 1.07–1.24. They also had 73% higher odds of a sedentary lifestyle, with an adjusted odds ratio of 1.73 and a 95% confidence interval of 1.59–1.87. The lower odds of substance use were also statistically significant: the adjusted odds ratio was 0.66, with a 95% confidence interval of 0.58–0.75, for at-risk alcohol use and 0.85, with a 95% confidence interval of 0.76–0.95, for smoking. By contrast, the adjusted odds ratio for non-good self-rated health was 1.05, with a 95% confidence interval of 0.93–1.18, indicating no statistically significant group difference. The available abstract did not provide an estimate for low fruit and vegetable consumption and described only no clear difference for that measure.

Because the analysis was cross-sectional, it cannot establish whether parental citizenship or another factor caused the observed differences. The supplied abstract also does not detail the measurement tools, response rates, missing-data procedures or survey-year-specific estimates, and it does not report whether associations differed by age group or parental country of origin. It likewise does not clarify whether having one foreign-citizen parent differed from having two. Based on the abstract, the overall pattern was mixed: higher odds of physical inactivity and excess weight accompanied lower odds of smoking and at-risk alcohol use, while self-rated health and fruit and vegetable consumption did not clearly differ between the groups. The authors identify longitudinal research on acculturation and parental country of origin as a priority for understanding these observed associations.

Subject of Research: Cross-sectional comparison of self-rated health and lifestyle behaviours among Italian survey participants aged 0–29 with and without foreign-citizen parents

Article Title: Self-rated health and lifestyle behaviours differences in second-generation migrants and Italians: an analysis of the daily life aspects surveys in Italy, 2015–2022

Article References: Siena, L. M., Sciurti, A., Di Napoli, A., Napoli, C., De Vito, C., Baccolini, V., & Petrelli, A. (2026). Self-rated health and lifestyle behaviours differences in second-generation migrants and Italians: an analysis of the daily life aspects surveys in Italy, 2015–2022. BMC Public Health. https://doi.org/10.1186/s12889-026-29837-1

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29837-1

Keywords: second-generation migrants, Italy, cross-sectional survey, self-rated health, overweight and obesity, sedentary lifestyle, alcohol use, smoking, fruit and vegetable consumption, health inequalities, Self-rated, health

The research team, led by Gül Eda Kılınç Tulum together with Yasemin Açar Kuru and Aliye Özenoğlu, set out with three linked goals: to characterize the feeding-related behaviors of children and adolescents with autism, to identify feeding-related factors from the perspective of caregivers, and to examine how nutritional status, quality of life, and behavioral problems relate to one another. Rather than relying on a single measure, the investigators assembled a battery of validated instruments, each targeting a different layer of the mealtime experience. The Brief Autism Mealtime Behavior Inventory, known as BAMBI, captured child mealtime behaviors; the Screening Tool of Feeding Problems, or STEP, flagged feeding difficulties; the Feeding Strategies Questionnaire documented parental approaches; the Quality of Life in Autism questionnaire, QoLA, assessed caregiver well-being; and a food frequency questionnaire charted dietary intake patterns.

The sample itself reflects the demographic profile often seen in pediatric autism research. The children and adolescents had a mean age of 8.98 years, with a standard deviation of 3.86, and three-quarters of them, 75.0 percent, were male. Perhaps more striking was the anthropometric finding: 33.3 percent of the participants were classified as overweight or obese according to World Health Organization growth references. This figure echoes a growing body of meta-analytic evidence showing that children with autism face elevated risks of excess weight gain, a pattern that may seem paradoxical in a population famous for picky eating but is consistent with diets dominated by energy-dense, highly processed, and palatable foods that survive even the strictest food selection filters.

On the BAMBI, the mean total score was 40.25 with a standard deviation of 8.24, and the sub-dimension analysis revealed where the trouble concentrates. The limited variety subscale scored highest at 20.6, with a standard deviation of 5.87, indicating that restricted food variety was the single most prominent feeding concern in this cohort. Food selectivity in autism is well documented in the broader literature; systematic reviews and large clinical cohorts have repeatedly found that children with autism accept fewer foods, reject entire food groups, and demand ritualized presentation far more often than their neurotypical peers. What the new study adds is a quantified hierarchy: within this sample, the narrowness of the accepted diet outweighed other mealtime behaviors such as food refusal or disruptive conduct at the table.

The STEP results told a complementary story. Among its sub-dimensions, nutrition-related behavioral problems achieved the highest mean score, 3.27 with a standard deviation of 3.12. This category encompasses difficulties that directly interfere with adequate nourishment, from refusing entire texture classes to vomiting or distress around specific nutrients and food types. Meanwhile, the Feeding Strategies Questionnaire revealed that the highest-scoring parental approach fell under child control of intake, with a mean of 19.33 and a standard deviation of 6.14. In practical terms, parents reported ceding substantial authority over what and how much their children eat. Clinicians will recognize this dynamic: when every meal risks a meltdown, allowing the child to dictate the menu can feel like the only sustainable path, even as it narrows the diet further and shifts the household’s nutritional baseline.

The statistical heart of the paper lies in its correlation analyses, which connect the child’s feeding profile to the parent’s lived experience. The BAMBI and STEP total scores were significantly and positively correlated, with a p-value of 0.009, meaning that children rated as showing more problematic mealtime behaviors were also flagged for more feeding problems on an independent instrument, a convergence that strengthens confidence in the measurement. More consequential for family well-being, the BAMBI total score was negatively correlated with the QoLA Part A score, which reflects the parent’s perception of the child’s quality of life, at p = 0.039. In other words, the more severe the mealtime behavior problems, the poorer parents rated their child’s overall quality of life, positioning feeding not as an isolated domain but as a lens through which families judge broader functioning.

The second key association ran in the opposite emotional direction. The STEP total score was positively associated with the QoLA Part B score, which measures parental quality of life and the burden parents experience, at p = 0.004. Because higher Part B scores on the QoLA correspond to greater difficulty and lower parental well-being, this finding indicates that more severe feeding problems were linked to worse caregiver quality of life. The mean QoLA scores in the sample, 91.0 with a standard deviation of 16.53 for Part A and 59.88 with a standard deviation of 19.27 for Part B, provide context for where these families sit on both dimensions. Together, the two correlations sketch a bidirectional picture: feeding problems color how parents see their child’s life, and they also erode the parents’ own well-being, a pattern consistent with prior research showing that mealtime stress is a significant contributor to caregiver strain in autism households.

The nutritional implications of such restricted eating are not trivial. The wider literature cited by the authors, including meta-analyses comparing dietary intake between children with autism and typically developing peers, documents inadequate intakes of several micronutrients, and scoping reviews have catalogued deficiencies in vitamins and minerals among selectively eating autistic children. In severe cases, case reports and case series have described nutritional deficiency diseases arising from avoidant and restrictive eating patterns associated with autism. The one-third of this sample classified as overweight or obese adds a second, seemingly contradictory risk layer, since energy-dense selective diets can simultaneously deliver excess calories and insufficient micronutrients. This double burden, overenergy alongside undernutrition, is increasingly recognized as a signature nutritional challenge in pediatric autism and underscores why routine growth monitoring and dietary assessment belong in standard care pathways.

The authors conclude that food selectivity and feeding problems are common in children and adolescents with autism spectrum disorder and are associated with lower parental quality of life for both the affected individuals and their caregivers, a conclusion they argue highlights the need for early, family-centered, multidisciplinary nutritional interventions. The emphasis on family-centered care is significant. Because the study found parents deferring to child control of intake, interventions that target the child alone may miss the relational dynamics that sustain restrictive eating. Multidisciplinary teams that combine dietitians, behavioral therapists, occupational therapists addressing sensory sensitivities, and clinicians monitoring gastrointestinal health are better positioned to broaden diets gradually while reducing the mealtime conflict that wears parents down.

As with all cross-sectional designs, the study captures associations rather than causal pathways, and its modest sample of 48 children means the findings are best read as a carefully measured snapshot rather than a definitive epidemiological estimate. Even so, the convergence of independent instruments, the alignment with international meta-analytic evidence on obesity and food selectivity in autism, and the explicit linkage between child feeding severity and caregiver quality of life give the results practical weight. For clinicians, the message is to screen for feeding problems early and treat them as a legitimate clinical target rather than a behavioral footnote. For parents exhausted by the nightly standoff over a single accepted brand of pasta, the study offers validation: the struggle at the table is real, measurable, and, importantly, treatable with the right support.

Subject of Research: Feeding problems, nutritional status, and parental quality of life in children and adolescents with autism spectrum disorder

Article Title: Beyond Food Selectivity: Feeding Problems, Nutritional Status, and Parental Quality of Life in Autism Spectrum Disorder

Article References: Kılınç Tulum, G. E., Açar Kuru, Y., & Özenoğlu, A. (2026). Beyond Food Selectivity: Feeding Problems, Nutritional Status, and Parental Quality of Life in Autism Spectrum Disorder. Journal of Autism and Developmental Disorders. https://doi.org/10.1007/s10803-026-07558-z

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07558-z

Keywords: autism spectrum disorder, food selectivity, feeding problems, nutritional status, parental quality of life, mealtime behavior, pediatric nutrition, overweight and obesity, BAMBI, STEP, QoLA, family-centered intervention

The team pursued a two-fold objective. First, they estimated the prevalence of the three principal forms of adolescent malnutrition, underweight, stunting, and overweight or obesity, and identified the socio-demographic determinants associated with each across Indian states. Second, they built scenario-based predictions of future malnutrition risk, with a particular focus on regional disparities across the four zones. This combination of descriptive epidemiology and predictive modelling is notable because adolescent nutrition has often been overshadowed in national policy by the intensive focus on the first thousand days of life, even though adolescence is a second window of rapid growth in which nutritional deficits and excesses can lock in lifelong health consequences.

Methodologically, the researchers relied on multivariable logistic regression, a statistical technique that estimates the association between each socio-demographic factor and a nutritional outcome while holding other variables constant. From the fitted models, they generated marginal predicted probabilities, which translate regression coefficients into concrete estimates of how likely an average adolescent in a given zone would be malnourished under hypothetical changes in key determinants such as household wealth, maternal and paternal education, and residence. The scenario-based approach effectively asks counterfactual questions: if poverty declined, or school completion rose, or healthcare access improved in a particular zone, by how much would predicted malnutrition risk shift?

The headline findings confirm a deeply uneven geography of malnutrition. Underweight was most prevalent in zone 4, affecting 30.25 percent of adolescents there, while stunting peaked in zone 3 at 33.29 percent. The authors report that these spatial disparities are driven primarily by lower educational attainment and lower household wealth. At the same time, the survey data reveal that the burden of malnutrition in India is no longer a story of undernutrition alone. Overweight and obesity emerged as a growing concern in zone 4, where 36.90 percent of adolescents were affected, with the rise concentrated particularly among adolescents from richer households. This coexistence of underweight and obesity within the same regions and even the same communities is the classic signature of the double burden of malnutrition, a phenomenon increasingly documented in low- and middle-income countries undergoing rapid economic and dietary transition.

The risk prediction analysis added a forward-looking dimension that distinguishes this study from conventional prevalence reports. The predicted risk map showed that zone 1 carries the highest probability of adolescent malnutrition, exceeding 0.4, a level the researchers attribute to high poverty, limited access to healthcare and persistent rural-urban disparities. Zone 3 followed with predicted risks in the range of 0.3 to 0.4, while zone 4 exhibited the lowest predicted risk, below 0.2. In practical terms, the model suggests that an adolescent living in the country’s poorest-resourced zone faces more than twice the predicted malnutrition risk of one living in the wealthiest zone, even before considering individual household characteristics.

The identification of specific socio-demographic determinants carries direct policy weight. Education and wealth function as the primary levers in the models: where parental schooling is limited and household assets are scarce, both underweight and stunting rise, whereas overweight and obesity climb along the wealth gradient, particularly in zones undergoing the fastest nutritional transition. This pattern implies that a single, uniform national nutrition strategy cannot serve all regions equally. An intervention designed to reduce underweight by boosting food security and household income may do little to slow, and could even accelerate, the rise of obesity in communities where caloric abundance and processed food access are increasing faster than nutritional literacy.

The authors argue that their zone-specific results point toward targeted, region-sensitive interventions. Underweight among adolescents should be prioritized in the northern and central parts of the country, stunting demands attention in the eastern region, and overweight and obesity require urgent action in the southern part of the nation. Mapping these three forms of malnutrition onto distinct geographic zones transforms the policy problem from an undifferentiated national target into a portfolio of regionally tailored programs, each with its own risk profile, delivery infrastructure and metric of success. The researchers further contend that integrating predictive analytics into public health planning can significantly improve policy responsiveness and the allocation of scarce resources, allowing program designers to anticipate where need will concentrate rather than reacting to prevalence data years after the fact.

The study also underscores why adolescence deserves greater analytical and programmatic attention in India. Data from the Comprehensive National Nutrition Survey, which was the first nationally representative nutrition survey to focus comprehensively on children and adolescents, show that nutritional insults accumulated during the second decade of life interact with pubertal growth, schooling outcomes and, eventually, the intergenerational transmission of health status. An adolescent girl who enters pregnancy stunted or underweight faces elevated risks of complications and of delivering a low-birth-weight infant, perpetuating a cycle that begins in the next generation. Conversely, adolescents who develop obesity face elevated lifetime risks of type 2 diabetes, cardiovascular disease and other non-communicable conditions, imposing a different but equally substantial burden on future health systems.

The technical machinery of the study, from its zone-level stratification to its marginal predicted probabilities, reflects a broader shift in population health research toward spatially explicit, forward-looking analysis. Where earlier surveys might have reported a single national prevalence figure, this work demonstrates how individual-level data from a comprehensive national survey can be recombined to expose the fault lines that matter for intervention design: which zone, which determinant, which form of malnutrition. The predicted risk figures, in particular, offer policymakers a quantitative template for prioritization, since a zone with predicted risk above 0.4 clearly warrants a different intensity of investment than one below 0.2, even if headline national averages appear moderate.

Limitations and caveats aside, the research lands at a moment when India is simultaneously confronting the residual challenges of undernutrition and the accelerating advance of diet-related chronic disease. The finding that overweight and obesity already affect nearly 37 percent of adolescents in the highest-burden zone, alongside underweight levels above 30 percent, captures the difficulty of that dual challenge in a single pair of numbers. The authors’ conclusion is measured but clear: predictive analytics embedded in nutrition policy, combined with interventions calibrated to the distinct epidemiology of each region, offer the most credible path to reducing adolescent malnutrition in all its forms. As the country’s demographic window of youth remains open for the coming decades, how effectively it responds to this divided nutritional map may shape the health of a generation.

Subject of Research: Spatial distribution and socio-demographic determinants of adolescent malnutrition in India using national nutrition survey data

Article Title: Spatial distribution and socio-demographic determinants of adolescent malnutrition in India using comprehensive national nutrition survey

Article References: Sharma, P., Javid, T., & Dwivedi, R. (2026). Spatial distribution and socio-demographic determinants of adolescent malnutrition in India using comprehensive national nutrition survey. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00457-9

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00457-9

Keywords: adolescent malnutrition, India, underweight, stunting, overweight and obesity, double burden of malnutrition, Comprehensive National Nutrition Survey, socio-economic determinants, spatial distribution, risk prediction, public health policy, regional disparities