The study used data from Spain’s national health surveys conducted in 2017, 2020 and 2023, including 22,038 responses in 2017, 22,077 in 2020 and 22,078 in 2023. It examined general practitioner visits, specialist consultations, hospital admissions and emergency department use across public and private sectors. Participants were classified into high, medium and low socioeconomic-status groups, and researchers fitted generalized linear models with negative binomial distributions and robust standard errors. Interaction terms tested whether socioeconomic patterns changed across survey years, while the analysis was also stratified by gender. The design was cross-sectional, so the results identify associations rather than demonstrating that socioeconomic position caused particular patterns of care.

Health need was the strongest influence across the different services, but it did not fully account for the observed inequalities. In primary care, low socioeconomic status was associated with higher utilisation, producing an incidence rate ratio of 1.11, with a 95% confidence interval of 1.01–1.22. Women also had higher primary-care use than men, with an incidence rate ratio of 1.21 and a 95% confidence interval of 1.18–1.25. The researchers found no significant interaction between socioeconomic status and survey year for primary-care use, indicating that this pattern was broadly stable across the study period.

Specialist care showed the opposite gradient. Compared with the high socioeconomic-status group, medium-status participants had an incidence rate ratio of 0.77, with a 95% confidence interval of 0.69–0.85, and low-status participants had a ratio of 0.70, with a 95% confidence interval of 0.63–0.78. Women reported more specialist use than men, with an incidence rate ratio of 1.23 and a 95% confidence interval of 1.1–1.28. Specialist use was also higher among Spanish nationals, with an incidence rate ratio of 1.13 and a 95% confidence interval of 1.05–1.21, and among people living with a partner. Relative to 2020, specialist use was higher in both 2017, with an incidence rate ratio of 1.38 and a 95% confidence interval of 1.19–1.61, and 2023, with a ratio of 1.21 and a 95% confidence interval of 1.02–1.42.

Hospital admissions were described by the researchers as being driven mainly by need. Although there was a significant interaction between socioeconomic status and survey year, with a p-value of 0.004, socioeconomic status had no independent effect in 2020. Emergency care displayed a time-dependent gradient: lower socioeconomic groups had higher emergency use in 2017 and 2020, but no such differences were detected in 2023. The interaction test was significant at p = 0.013. Emergency use in 2023 was 19% higher than in 2020, with an incidence rate ratio of 1.19 and a 95% confidence interval of 1.01–1.41. Taken together, the results suggest that the broader pattern of more primary and emergency care but less specialist care among lower-status groups remained recognizable around the COVID-19 pandemic period, even though some service-specific patterns varied by year.

Subject of Research: Socioeconomic inequalities in healthcare service utilisation in Spain from 2017 to 2023

Article Title: Socioeconomic inequalities in health service utilisation in Spain: a population-based analysis of national health surveys data (2017–2023)

Article References: Martín-Fernández, J., Polentinos-Castro, E., Alonso-Safont, T., Olmedo-Galindo, J., Rodríguez-Martínez, G., Ariza-Cardiel, G., & del-Cura-González, I. (2026). Socioeconomic inequalities in health service utilisation in Spain: a population-based analysis of national health surveys data (2017–2023). BMC Health Services Research. https://doi.org/10.1186/s12913-026-15543-6

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15543-6

Keywords: health inequalities, Spain, healthcare use, national health surveys, primary care, specialist care, emergency care, socioeconomic status, COVID-19, Socioeconomic, inequalities, health

The age-standardized incidence rate declined from 40.70 to 37.59 cases per 100,000 population between 2000 and 2023. The age-standardized mortality rate fell from 19.80 to 15.65 deaths per 100,000, and the age-standardized DALY rate decreased from 344.34 to 271.00 per 100,000. The researchers described the combination of rising totals and falling standardized rates as consistent with population aging and demographic growth.

The study used Global Burden of Disease Study 2023 estimates to examine national and subnational trends in prostate cancer incidence, mortality and disability burden. It evaluated changes from 2000 through 2023 with weighted log-linear models and calculated annual percentage changes (APCs). These are modeled population-level estimates rather than direct measurements of every case, death or health outcome among men in Mexico.

National trends did not fully represent conditions in individual states. The researchers found considerable geographic heterogeneity across the 32 states and assessed its relationship with socioeconomic conditions using the 2020 marginalization index developed by Mexico’s National Population Council. Spearman correlation analyses tested whether state-level marginalization was associated with estimated prostate cancer burden in 2023 and with the pace of change over the study period.

More marginalized states had lower estimated age-standardized prostate cancer burden in 2023. Marginalization was negatively correlated with the age-standardized incidence rate (ρ = −0.556, p = 0.001), age-standardized mortality rate (ρ = −0.471, p = 0.007) and age-standardized DALY rate (ρ = −0.485, p = 0.005). These associations show that, at the state level, greater socioeconomic marginalization coincided with lower modeled rates in the final year of the analysis.

State-level marginalization was also associated with slower improvement over time. It correlated positively with less favorable APCs for incidence (ρ = 0.555, p = 0.001), mortality (ρ = 0.514, p = 0.003) and DALYs (ρ = 0.467, p = 0.007). The pattern means that states with lower estimated age-standardized burden in 2023 did not necessarily show the strongest reductions across the 24-year period; more marginalized states generally progressed more slowly on all three measures.

The findings carry an important limitation because the analysis did not measure diagnostic coverage, cancer-registration completeness, disease stage, treatment access or healthcare utilization. Consequently, lower estimated rates in highly marginalized states cannot be taken as evidence that the underlying risk of prostate cancer or death from it was lower. Incomplete detection or surveillance is one possible explanation for lower recorded rates, but the study could not determine how much of the geographic pattern reflected differences in disease, ascertainment or other factors.

The correlations are also ecological associations based on state-level data. They do not establish that marginalization directly caused the differences in estimated burden or rates of improvement, and they do not by themselves demonstrate differences in health-system performance. The study instead documents two distinct features of the modeled data: more marginalized states had lower estimated age-standardized burden in 2023, but less favorable trends from 2000 to 2023.

Together, the results indicate persistent geographic and socioeconomic differences within Mexico despite national declines in age-standardized incidence, mortality and DALY rates.

Subject of Research: State-level socioeconomic associations with prostate cancer burden and trends in Mexico from 2000 to 2023

Article Title: Subnational inequalities and socioeconomic gradients in prostate cancer burden across Mexico, 2000–2023

Article References: Guzmán-Esquivel, J., Hernández-Fuentes, G. A., Hernandez-Suarez, C. M., Pineda-Urbina, K., Delgado-Enciso, J., Romero-Michel, J. C., Rojas-Larios, F., Meza‑Robles, C., Cabrera-Licona, A., Montesinos-López, O. A., Rodríguez-Hernandez, A., & Delgado-Enciso, I. (2026). Subnational inequalities and socioeconomic gradients in prostate cancer burden across Mexico, 2000–2023. Cancer Causes & Control, 37(11), Article 183. https://doi.org/10.1007/s10552-026-02258-6

Image Credits: AI Generated

DOI: 10.1007/s10552-026-02258-6

Keywords: prostate cancer, Mexico, health inequalities, marginalization, GBD 2023, age-standardized rates, cancer mortality, regional disparities, cancer surveillance, disability-adjusted life years, Subnational, inequalities

The researchers analysed anonymised records from the Clinical Practice Research Datalink Gold and Aurum datasets, which cover approximately 60 million patients, or about 20% of the UK population, through more than 2,400 general practices. These records were linked to Hospital Episode Statistics for admissions and outpatient and emergency care, as well as Office for National Statistics death registrations. Adults with MS were matched to up to 10 controls without MS on general practice, sex and year of birth, and controls were assigned the same index date as their matched MS case.

MS was identified through two or more diagnostic or management codes, or one MS code accompanied by an appropriate prescription. Diabetes was defined as suspected or confirmed type 1, type 2 or unspecified diabetes, with or without antidiabetic medication; people whose only record was gestational diabetes were excluded. A six-month wash-out period after the MS diagnosis date was used to reduce the chance that hospitalisations were directly related to the diagnostic process. The models adjusted for age, sex, ethnicity, area-level deprivation, rural or urban residence, smoking status and practice-level random effects, with additional sensitivity analyses restricting the MS group to diagnoses made from 2002 onward and considering confirmed diabetes only.

Over the study period, 2,119 people with MS, or 4.48%, developed suspected or confirmed diabetes, compared with 21,720 controls, or 4.73%. The crude incidence rate was 3.14 per 1,000 person-years for people with MS and 3.00 per 1,000 person-years for controls. After adjustment, the incidence rate ratio was 1.16, meaning the observed rate among people with MS was about 16% higher than among matched controls, with a 95% confidence interval of 1.11 to 1.21. The association was similar when diabetes was analysed with a cause-specific Cox model and when baseline hypertension was added to the adjustment set. Diabetes type was available for only 35.79% of people with incident diabetes, but the increased incidence was observed in both recorded type 1 and type 2 groups.

Diabetes was associated with substantially greater use of hospital services among people with MS. In unadjusted models, those with incident diabetes had 2.83 times as many hospitalisation episodes as MS patients without incident diabetes. The association was smaller after adjustment, but remained clear: the adjusted incidence rate ratio was 1.52, with a 95% confidence interval of 1.42 to 1.64. The result was unchanged when the analysis was restricted to MS diagnosed from 2002 onward, when only confirmed diabetes was counted, or when hypertension was included as an additional covariate. Hospitalisation duration was also longer among MS patients with incident diabetes. The median cumulative duration of hospital admissions was 12 days, with an interquartile range of 0 to 83 days, for those with diabetes, compared with 2 days, with an interquartile range of 0 to 22, for those without diabetes. The adjusted regression coefficient was 0.89, and the association persisted in the sensitivity analyses.

Controls showed an even stronger relationship between incident diabetes and hospitalisation. Among controls, the adjusted incidence rate ratio for the number of admissions was 2.36, and the adjusted association with hospitalisation duration was also significant. When both groups were examined together, the diabetes-related excess in hospitalisation episodes was stronger among controls than among people with MS, with an interaction estimate of 0.43 and a 95% confidence interval of 0.40 to 0.47. The difference for hospitalisation duration was likewise stronger in controls. The researchers suggested that admissions related to MS itself may dilute the relative effect of diabetes among MS patients. Another possible explanation is closer monitoring of people with MS, although that possibility was not directly tested, and the data did not show a corresponding reduction in mortality.

Diabetes was also associated with higher all-cause mortality among people with MS. In the primary model, incident diabetes was associated with an adjusted hazard ratio of 1.08 for death, with a 95% confidence interval of 1.01 to 1.15. When diabetes was modelled as a time-varying exposure, the hazard ratio was higher, at 1.41, with a 95% confidence interval of 1.31 to 1.49. This model was intended to reduce immortal time bias by accounting for the time before diabetes developed. The association remained significant in analyses limited to MS diagnosed from 2002 onward, when diabetes was restricted to confirmed cases, and after further adjustment for hypertension. In controls, incident diabetes was associated with mortality as well, with an adjusted hazard ratio of 1.25 in the primary analysis and 1.69 when diabetes was modelled as time-varying.

The mortality association did not differ significantly between people with MS and controls. The interaction between MS status and incident diabetes was not statistically significant in the main mortality model, nor when diabetes was treated as a time-varying exposure. Thus, the study does not show that diabetes has a uniquely stronger or weaker effect on death in people with MS than in comparable people without MS. It does show that, in both populations, the emergence of diabetes was associated with a higher subsequent risk of dying. The findings should therefore be interpreted as observational associations rather than proof that diabetes caused the excess hospital use or mortality.

Interaction analyses found limited evidence that ethnicity, deprivation or rural–urban residence modified the overall relationships in the MS cohort. Within people with MS, however, the association between diabetes and the number of hospitalisation episodes was stronger among people living in rural areas. Among controls, the relationship was stronger in White than non-White groups for some hospitalisation measures, and diabetes-related mortality was stronger among people in the least deprived groups and in rural areas. These subgroup findings came from smaller numbers and require caution. The study authors noted that regular healthcare contact among people with MS could increase detection of asymptomatic diabetes and partly contribute to the higher observed incidence in the MS group. Baseline comorbidity, physical activity, obesity, immune dysregulation and shared autoimmune susceptibility for type 1 diabetes were discussed as possible explanations, but the mechanisms were not established.

Several limitations constrain the interpretation and generalisability of the results. The database relies on routinely collected clinical information, so some conditions may be under-recorded, ethnicity was missing for some participants, and people who are less engaged with healthcare services may be underrepresented. Diabetes type was unrecorded for 64% of people with incident diabetes, and haemoglobin A1c was not reliably available for analysis. People who develop diabetes may differ from those who do not in ways that were not fully measured, so residual confounding cannot be excluded. The MS index date was the first recorded code rather than the date of clinical onset, and disease duration before that point was therefore unknown. Finally, the cohort was predominantly White and based in England, while the epidemiology of MS and diabetes differs by geography and ethnicity, limiting extrapolation to other populations. The authors concluded that further studies are needed and that equity-informed diabetes screening, prevention and management may benefit people with MS.

Subject of Research: Associations between incident diabetes, hospitalisation and mortality in people with multiple sclerosis

Article Title: Incident Comorbid Diabetes and Outcomes in Multiple Sclerosis: An English Population‐Based Cohort Study

Article References: Lau, Y., Zabihi, S., Hartmann, M., Mathlin, G., Banerjee, S., Marouf, E., Hadley, C., Cooper, C., & Dobson, R. (2026). Incident Comorbid Diabetes and Outcomes in Multiple Sclerosis: An English Population‐Based Cohort Study. Annals of Clinical and Translational Neurology, Article acn3.70548. https://doi.org/10.1002/acn3.70548

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DOI: 10.1002/acn3.70548

Keywords: multiple sclerosis, incident diabetes, hospitalisation, mortality, population-based cohort, English health records, health inequalities, observational study, type 2 diabetes, Incident, Comorbid, Diabetes

The investigation followed the detection in late 2023 of a small cluster of tuberculosis cases among men of sub-Saharan origin living in Badalona. Several cases were linked to the occupied building, and another resident was subsequently hospitalized with disseminated tuberculosis and died during admission. The field investigation was coordinated by the Epidemiological Surveillance Service of Barcelonès Nord and Maresme with primary care, hospital and community teams, and was designed to identify undiagnosed active disease and assess the feasibility of outreach screening in a structurally vulnerable population.

Conditions in the building included overcrowding, poor ventilation, makeshift partitions, and limited access to water and electricity. In addition to people residing there, the building served as a social, religious and community gathering place, so the eligible population included regular non-resident users. Population estimates were uncertain and changed between visits; women and children were initially not known to be present, while people who used cannabis and alcohol were present in both sections of the building.

Three sequential on-site interventions combined health education, symptom-based screening and clinical assessment. Recruitment involved posters, word of mouth, visits by community health workers and support from trusted community representatives. The symptom questionnaire covered unexplained cough, unexplained fever lasting more than three weeks, night sweats, dyspnea, chest pain, unintentional weight loss and unexplained fatigue. People reporting symptoms and close contacts of cases were assessed clinically, while asymptomatic close contacts were referred for chest radiography. Referrals for suspected tuberculosis included chest radiography, sputum smear microscopy, culture and Xpert MTB/RIF Ultra testing under national protocols. Transportation cards and community-worker support were provided to facilitate access.

Across the three visits, 81 people were screened, equivalent to 54% of the estimated eligible population. Forty-five completed symptom questionnaires and clinical examinations, among whom 12 were classified as presumptive tuberculosis cases, a positivity of 27%. All 12 completed diagnostic evaluation, producing 100% retention in testing. Three were diagnosed with tuberculosis, giving a number needed to screen of 27 and a number needed to test of 4. Two began treatment, completed it and were cured; the third, a probable lymph node tuberculosis case, never started treatment and was lost to follow-up. Treatment outcomes were assessed through April 2026.

The October 2024 intervention reached 55 male participants, of whom 19 completed full clinical assessments. Two new smear-positive pulmonary tuberculosis cases were diagnosed after all seven people evaluated for suspected disease had received radiography, with one evaluated at primary care after missing a hospital appointment. The November intervention included 25 participants and 13 asymptomatic close contacts, resulting in one additional probable lymph node tuberculosis diagnosis. A February 2025 outreach effort identified 12 women and seven children linked to the settlement, but only one woman attended evaluation; no children were screened. She had previously received tuberculosis treatment and had a normal chest X-ray.

Beyond the three cases detected through screening, surveillance and hospital records identified six additional linked cases, bringing the total to 11. These included the index case, the fatal disseminated case, the two pulmonary cases found in the first intervention, the probable lymph node case found in the second, and six additional cases. During the ascertainment period, another 66 residents who had not been screened for tuberculosis and had no previous public health system record registered with and attended the Sant Roc Primary Care Center following community engagement and referral activities. Three children were also linked to pediatric primary care for health needs unrelated to tuberculosis screening.

Participation was limited by population mobility, incomplete enumeration, institutional mistrust, weak coordination with social services and limited transport and accompaniment support. Women and children were markedly underrepresented, and field professionals informally reported concerns that some women feared contact with public health services could draw the attention of social services. Site identification was delayed by six months after the initial reported cases, and incomplete mapping required another four months before the first intervention. An eviction notice issued during the campaign prompted residents to leave or relocate, contributing to loss to follow-up and unscreened people.

The investigation was descriptive and limited to one occupied building and its connected community. It did not include on-site chest radiography, so symptomatic participants and close contacts were referred to healthcare facilities, although all 12 presumptive cases completed diagnostic evaluation. The estimated eligible population remained uncertain, coverage differed across the three visits, and the findings cannot establish the effectiveness or cost-effectiveness of screening in comparable settlements. The authors nevertheless observed that coordinated community outreach detected active disease and linked residents with healthcare services, while concluding that such screening remains operationally fragile in the presence of housing instability, mobility, mistrust and limited institutional support.

Subject of Research: Descriptive field investigation of community tuberculosis screening in an informal urban settlement in Badalona, Spain.

Article Title: Tuberculosis transmission and community outreach screening in an informal urban settlement in a low-incidence European setting

Article References: Flamarich-Gol, C., Bosch-Arís, M., Blázquez, G., Garcia-Circuns, A., Thiaw, B. E., Essadek, H. O., Roure, S., Stojanovic, Z., Bellido-Calduch, S., Lovera, M., García-Delgado, A., Segura, A., Carreres-Molas, A., Guasch-Arriaga, I., Antuori, A., Llop, A., Pillado, P., Romero, Y., Antolín, O., … Vilaplana, C. (2026). Tuberculosis transmission and community outreach screening in an informal urban settlement in a low-incidence European setting. Frontiers in Public Health, 14, Article 1907926. https://doi.org/10.3389/fpubh.2026.1907926

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1907926

Keywords: tuberculosis, community screening, active TB, outreach, informal housing, Badalona, public health surveillance, health inequalities, contact tracing, transmission, community, screening

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

Published in BMC Health Services Research , the review followed PRISMA 2020 guidelines and was registered with PROSPERO under the identifier CRD42024572294. The authors described inclusive implementation, tailored delivery of e-health applications, and support in using e-health as elements that could help address the digital divide between people with low and high socio-economic positions. For the systematic search, researchers used five databases: PsycINFO, Web of Science, Embase, PubMed and Sociological Abstracts.

Search terms were built around three core concepts: socio-economic position, e-health and delivery strategy. The search produced 5,127 papers after duplicates were removed, from which the researchers included 35 papers describing 33 studies. To compare the varied approaches, the review classified delivery strategies into five components: place, point of contact, promotion, facilitation and incentive.

The analysis showed that almost all identified strategies combined multiple components. Place and point-of-contact strategies were most frequently applied and often used together. These findings concern the delivery and reach of digital health rather than the clinical effectiveness of the e-health applications themselves.

The review therefore does not establish that any application improved health outcomes, nor does it demonstrate that one delivery strategy consistently outperformed another. The authors described the findings as insights into potentially effective approaches rather than conclusive proof of a preferred method. Reported design underpinnings were limited.

Stakeholder involvement was identified as an applied principle for implementation-strategy design, together with the identification and operationalization of specific delivery strategies. However, the studies rarely explained whether these strategies were based on established theory or accumulated experience. Overall, the review identifies a gap in evidence about effective e-health delivery for people with a low socio-economic position.

Its findings show that digital health delivery commonly depends on combinations of place, contact, promotion, facilitation and incentives, with place and point of contact appearing most often. The limited and dispersed evidence indicates potential approaches, but definitive conclusions require stronger evaluations of delivery strategies in real-world settings.

Subject of Research: Delivery strategies and reported reach of digital health for people with a low socio-economic position

Article Title: A systematic literature review to identify delivery strategies of digital health for low SEP populations

Article References: Bartha Standaar, L. M., van der Vaart, R., Leenaars, K., Friele, R. D., & van Tuyl, L. H. D. (2026). A systematic literature review to identify delivery strategies of digital health for low SEP populations. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15442-w

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DOI: 10.1186/s12913-026-15442-w

Keywords: digital health, e-health, health inequalities, socio-economic position, systematic review, digital divide, implementation, health services, stakeholder involvement, literature review, systematic, literature

Researchers analysed Clinical Practice Research Datalink Aurum primary care records linked with Hospital Episode Statistics for patients registered on 1 April 2018. Diagnoses recorded over the preceding 12 years in primary and secondary care were used to estimate prevalence for each condition. Estimates were calculated by area-level deprivation quintile, age group and sex. The investigators then compared the most and least deprived quintiles using absolute prevalence gaps and relative prevalence ratios, and compared estimates based on primary care alone with those based on linked primary and secondary care records.

Socioeconomic inequalities in prevalence were widespread but not uniform across the 209 conditions. Most conditions had higher estimated prevalence in the most deprived quintile, including obesity, hypertension, depression, anxiety disorders, and alcohol or substance misuse. The proportion of conditions showing higher prevalence in more deprived quintiles was highest among patients aged 40–59 years, followed by those aged 60–79 years. A smaller number of conditions showed the opposite pattern: raised total cholesterol was more prevalent in less deprived groups among patients aged 60 years and over, while all cancers combined also had higher prevalence in less deprived groups. Individual cancer conditions displayed heterogeneous patterns, so the combined cancer estimate did not represent every cancer in the same way.

Care setting was associated with the scale of the measured differences. Linked primary and secondary care records generally yielded larger absolute prevalence gaps than primary care records alone. Including secondary care data also increased the proportion of conditions with higher prevalence in the most deprived quintile in every age–sex group. The findings therefore show that estimates based on linked records differed from those based on primary care alone, without establishing the mechanism behind that difference. As a descriptive analysis of diagnoses recorded in routine care, the study measured differences in recorded prevalence across deprivation groups rather than directly measuring every participant’s underlying health status. Its scope was England, 209 chronic conditions, and 12.7 million patients in primary care linked to hospital data; the supplied findings do not provide estimates of prevalence changes over time or establish causal effects.

The work is described by the authors as the first national systematic assessment of prevalence by area-level deprivation across 209 chronic conditions recorded in primary or secondary care in England. By examining conditions individually, the study documents both widespread inequalities and notable exceptions. The authors said the condition-specific descriptive estimates could support more tailored analyses accounting for socioeconomic differences in disease burden and case mix, as well as targeted prevention, public health planning, routine monitoring of inequalities, resource allocation and evaluations of interventions. Those proposed uses follow from the study’s broad descriptive scope rather than evidence that any particular intervention reduced a prevalence gap.

Subject of Research: National linked-record analysis of chronic-condition prevalence by area-level deprivation in England

Article Title: Prevalence of 209 chronic conditions by area-level deprivation in England

Article References: Wang, S., & Anselmi, L. (2026). Prevalence of 209 chronic conditions by area-level deprivation in England. BMC Public Health. https://doi.org/10.1186/s12889-026-29718-7

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29718-7

Keywords: health inequalities, chronic diseases, area-level deprivation, England, primary care, secondary care, linked health data, disease prevalence, socioeconomic disparities, public health, Prevalence, chronic

The research team, led by Yuval Arbel of Western Galilee College together with Israel Rachevski, Amichai Kerner of Bar Ilan University, and Miryam Kerner of the Technion and Kaplan Medical Center, assembled municipality-level administrative data covering roughly 96 percent of Israel’s 132 municipalities. Their outcome measure was age-standardized diabetes prevalence—the number of diagnosed diabetes cases per 1,000 inhabitants, adjusted to remove distortions from differing age structures—based on 2017 to 2019 data. Socioeconomic status came from the official municipal ranking published by the Israeli Central Bureau of Statistics, a composite index reflecting income, education, employment, and living conditions on a scale from 1, the most disadvantaged, to 10. Population density, measured in inhabitants per square kilometer, served as the proxy for urban context.

The descriptive picture alone is striking. Average diabetes prevalence across the sample was 68.71 cases per 1,000 inhabitants, but the range ran from 38.27 in the healthiest municipality to 142.84 in the most affected—more than a threefold difference. The bivariate statistics told a familiar story: diabetes prevalence correlated strongly and negatively with socioeconomic rank, with a Pearson coefficient of −0.633, and negatively with logged population density at −0.273. But the researchers were not content to stop at correlation. Their central question was whether the shape of the socioeconomic gradient itself changes as density changes, and answering that required a more flexible statistical architecture.

Their approach was an ordinary least squares regression with a quadratic specification: diabetes prevalence was modeled as a function of socioeconomic rank, the square of that rank, the natural logarithm of population density centered at the sample median of about 2,713 inhabitants per square kilometer, and—crucially—interaction terms between density and both the linear and squared SES components. Those interactions allow the slope and the curvature of the SES–diabetes relationship to vary with density, rather than forcing a single gradient onto all 127 municipalities. Heteroskedasticity-robust HC3 standard errors guarded against undue influence from outlying municipalities in the relatively small cross-section. The model explained about 44 percent of the between-municipality variation in diabetes prevalence.

The headline result concerns what density does at the bottom of the socioeconomic distribution. At SES rank 1, the marginal effect of logged density was −14.73, statistically significant at the one percent level, meaning that an exact 10 percent increase in population density was associated with roughly 1.40 fewer diabetes cases per 1,000 inhabitants. At rank 2 the effect was −9.66, equivalent to about 0.92 fewer cases per 1,000 for the same density increase, and at rank 3 it remained significant at −5.64, or roughly 0.54 fewer cases. From rank 4 onward, the density association dissolved into statistical noise, hovering near zero across the middle and upper reaches of the SES scale. In other words, the apparent protective association of urban density is concentrated precisely where diabetes burden is highest.

The complementary analysis examined how the SES gradient itself shifts across density contexts, evaluating conditional coefficients at the 25th percentile (1,927 inhabitants per square kilometer), the median (2,713), and the 75th percentile (4,531) of the density distribution. At the two lower density levels, neither the linear nor the quadratic SES component reached statistical significance. But at the 75th-percentile density, the conditional quadratic coefficient turned substantially more negative, at −0.628, and became significant at the five percent level. The researchers calculated that this detectable curvature emerges at densities above approximately 4,227 inhabitants per square kilometer—though they are careful to frame this as an approximate density region, not a discrete threshold. Predicted curves plotted at the three density levels fan out dramatically at the low end of the SES distribution and converge in the middle and upper portions, visual confirmation that density matters most for the most disadvantaged places.

One subtlety deserves emphasis, because it guards against an overly enthusiastic reading. At high density, the estimated turning point of the quadratic relationship sits at approximately SES rank 1.05—almost exactly the bottom boundary of the observed scale. That means the data do not support characterizing the high-density relationship as a broad inverted-U in which intermediate socioeconomic levels carry the greatest risk. Instead, predicted diabetes prevalence peaks near the very bottom of the SES range and declines across virtually the entire remaining distribution. The quadratic evidence, the authors note, should be interpreted cautiously; the parsimonious quadratic form imposed on an ordinal nine-level ranking cannot uniquely identify the true functional form of the SES–diabetes relationship.

What might explain the pattern? The authors are explicit that their observational design cannot establish causation, and that population density should not be read as the causal mechanism itself. Rather, density likely serves as a proxy for a bundle of municipal characteristics: proximity to services, transportation accessibility, healthcare infrastructure, demographic composition, and the walkability and service provision that urban economists associate with agglomeration. For socioeconomically disadvantaged residents, who may lack private vehicles and face constraints on healthcare access, the resources concentrated in denser municipalities could matter disproportionately. The interpretation aligns with a substantial place-effects literature in health geography, as well as emerging evidence that the built environment and socioeconomic context interact in non-linear ways to shape obesity and diabetes risk. At the same time, density brings its own exposures, and the same urban form that puts clinics within walking distance can also concentrate pollution and alter consumption environments.

The policy implications cut against entrenched practice. If municipalities with identical socioeconomic rankings can carry markedly different disease burdens depending on their density context, then allocating preventive resources by rank alone risks misallocation. Two disadvantaged municipalities—one sprawling and sparse, one compact and dense—may not need the same intervention intensity, even though their composite SES scores are indistinguishable. The authors recommend complementing socioeconomic indices with direct, outcome-based indicators such as observed disease prevalence, identifying municipalities whose burden is unexpectedly high relative to their rank and local characteristics, and incorporating density and other contextual variables into the design of screening and lifestyle interventions. For chronic disease prevention, where risk factors are tightly entangled with environmental and behavioral conditions, such flexibility may be especially consequential.

The study carries limitations that shape how far its conclusions travel. Five municipalities with missing data were excluded, leaving open the possibility of some selection; the analysis is cross-sectional and cannot disentangle behavioral, environmental, and institutional confounders; and because observations are municipalities rather than individuals, the findings describe between-place differences, not individual-level associations between a person’s socioeconomic status and their diabetes risk. Residual confounding by unmeasured municipal characteristics cannot be excluded even with age standardization. Still, the core message is difficult to dismiss: socioeconomic gradients in health may not operate uniformly across space, and the interactive structure the Israeli data reveal offers a template for testing whether the same density-dependent heterogeneity appears in other countries and for other outcomes. If it does, the humble practice of ranking places by wealth and intervening accordingly may need a considerably more textured replacement.

Subject of Research: The relationship between municipal socioeconomic status, population density, and diabetes prevalence in Israel

Article Title: Socioeconomic gradients in diabetes prevalence across Israeli municipalities: the role of population density

Article References: Arbel, Y., Rachevski, I., Kerner, A., & Kerner, M. (2026). Socioeconomic gradients in diabetes prevalence across Israeli municipalities: the role of population density. Frontiers in Epidemiology, 6, Article 1848489. https://doi.org/10.3389/fepid.2026.1848489

Image Credits: AI Generated

DOI: 10.3389/fepid.2026.1848489

Keywords: diabetes prevalence, socioeconomic status, population density, health inequalities, Israel, municipalities, epidemiology, public health policy, urban health, chronic disease prevention, place effects, quadratic regression

The research, led by Dixie Brea Larios of the Oral Health Centre of Expertise in Western Norway, together with Anne N. Åstrøm of the University of Bergen and Manal Mustafa of the University of Bergen and the Oral Health Centre of Expertise, set out to examine the oral health practices of parents with and without a migrant background. The motivation is grounded in a well-documented problem: the migration process itself often pushes oral health down the list of priorities, and the consequences can persist for years after resettlement. Dental problems accumulate quietly, and by the time they surface, they can affect nutrition, speech, employment, and self-confidence.

To capture a representative picture, the team used a cross-sectional survey of parents with children in either kindergarten or elementary school. The sample comprised 600 participants, evenly split between 300 migrants and 300 Norwegian-born parents. Respondents answered questions about how they perceived their own oral health, their sociodemographic circumstances, their history of dental visits, and their dietary habits. The mean age of participants was 39.11 years, with a standard deviation of 6.45 years, and women made up 62 percent of the study population. Self-rated oral health, the study’s central outcome measure, is a deceptively simple question with considerable scientific weight: decades of epidemiological work have shown that how people rate their own mouths correlates with clinically measured disease, dental attendance patterns, and even broader quality of life.

The statistical analysis yielded a result that cuts against common assumptions. Migrant status was not a significant predictor of self-reported oral health, with an odds ratio of 0.93 and a p-value of 0.667, meaning the difference between migrants and non-migrants could easily have arisen by chance. In plain terms, knowing whether a parent was a migrant told the researchers almost nothing about how that parent rated their teeth and gums. What did matter were two variables that applied to everyone in the sample. Participants who attended dental check-ups had dramatically lower odds of reporting poor oral health, with an odds ratio of 0.25 and a p-value below 0.001, translating to a 75 percent reduction in the odds of worse self-rated oral health compared with those who did not attend. Educational attainment also played a significant role, with an odds ratio of 1.64 and a p-value of 0.001, indicating that more educated parents were substantially more likely to report better oral health.

One subgroup finding added nuance to the picture. Participants originating from Asian regions had 57 percent lower odds of reporting worse oral health than the reference group. This kind of regional variation within the migrant population is itself instructive, because it demonstrates that migrants are not a homogeneous block. Aggregating all migrant groups into a single category can obscure real differences in oral health profiles, dietary patterns, and experiences with dental services. The Norwegian study’s ability to detect such variation reflects both its sample size and its analytical approach, which modeled multiple sociodemographic and behavioral factors simultaneously rather than examining migrant status in isolation.

The strength of the dental attendance association deserves particular attention. An odds ratio of 0.25 is a large effect by the standards of public health epidemiology, where behavioral predictors often hover near 1.0 and are celebrated when they reach 1.2 or 1.5. Regular dental visits are associated with early detection of caries, professional cleaning, fluoride application, and preventive counseling, all of which interrupt the trajectory of oral disease before it becomes painful or irreversible. Conversely, people who avoid dental care tend to present only when problems are acute, reinforcing negative experiences and deepening avoidance. The study’s cross-sectional design means the direction of this relationship cannot be definitively established, since people with healthy mouths may simply have less reason to visit the dentist, but the association aligns with a large body of clinical evidence on the benefits of consistent preventive care.

Education, the other strong predictor, operates through several plausible mechanisms. Higher educational attainment is consistently linked with greater oral health literacy, better understanding of preventive recommendations, more stable incomes that make dental fees manageable, and workplaces that accommodate time off for appointments. In Norway, where the public dental health service provides free care to children but adults generally pay out of pocket for treatment, the educational gradient in adult oral health reflects both knowledge and economic access. The finding that education mattered equally across migrant and Norwegian parents suggests that these mechanisms are not specific to any cultural group but are structural features of how societies distribute health resources.

The authors are careful about what their results do and do not imply. They do not claim that migration is irrelevant to oral health; rather, they conclude that being a migrant is not the primary factor affecting oral health outcomes in this population. Instead, it is the interplay of sociodemographic factors, health behaviors, and access to dental care that plays the significant role. This distinction matters for policy. Interventions designed around migrant status as the central risk factor may miss the levers that actually move outcomes, such as reducing barriers to dental attendance and addressing educational inequalities. At the same time, the researchers acknowledge that various barriers can influence parental oral health behaviors during the migration process, and that prioritizing oral health and access to dental services remains essential for everyone.

The study forms part of a broader research effort in Norway to build an evidence base for improving oral health services, oral health literacy, and responsiveness to migrant needs. It was conducted within the COP study, Caries and Obesity Prevention in Children with a Migrant Background, financed by the Norwegian Research Council under grant number 331782. The survey data came from the Folkehelseundersøkelse i Vestland 2022, the national public health survey in Vestland county, accessed through the Norwegian health data infrastructure. Ethical approval for data access and handling was obtained from the Regional Committee for Medical and Health Research Ethics and the Norwegian Agency for Shared Services in Education and Research. The work also received support from the Research Department at the Oral Health Centre of Expertise in Western Norway.

The practical implications reach beyond Norway’s fjords. Migrant populations across Europe and North America are growing, and health systems everywhere are grappling with how to serve them equitably. This study offers a deceptively simple lesson: the path to better oral health may run through the same channels for everyone, namely affordable and consistent dental care and the education that helps people value and navigate it. The authors recommend that health authorities strengthen family- and community-based strategies embedded within broader health promotion and preventive programs, and they call for further research measuring oral health behaviors and oral health literacy to illuminate the mechanisms at play. If the goal is to reduce disparities, the evidence from Western Norway suggests that the starting point is not where people come from, but whether they can and do get to a dental chair.

Subject of Research: Associations between sociodemographic factors, dental care utilization, dietary habits and self-rated oral health among parents with and without a migrant background in Western Norway

Article Title: Self-rated oral health among parents with and without a migrant background in Western Norway: associations with sociodemographic factors, dental care utilization, and dietary habits

Article References: Brea Larios, D., Åstrøm, A. N., & Mustafa, M. (2026). Self-rated oral health among parents with and without a migrant background in Western Norway: associations with sociodemographic factors, dental care utilization, and dietary habits. BMC Public Health. https://doi.org/10.1186/s12889-026-29789-6

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29789-6

Keywords: oral health, self-rated health, migrant health, dental attendance, dental care utilization, health inequalities, public health, Norway, parents, sociodemographic factors, dietary habits, dental epidemiology

The review, conducted by researchers at the Sussex Health Outcomes Research and Education in Cancer group at Brighton and Sussex Medical School, followed the Joanna Briggs Institute methodology for scoping reviews. The team searched five major databases, PsycInfo, PubMed, Embase, CINAHL and Scopus, alongside grey literature sources including theses, conference abstracts and cancer charity publications, with no date restrictions. After removing 1,301 duplicates from an initial haul of 3,314 records and screening nearly 2,000 titles and abstracts, only five studies survived full-text review. Four more emerged from grey literature and citation searching, bringing the total to nine, two of which reported on the same sample. Seven were qualitative, one quantitative and one mixed-methods, conducted between 2009 and 2024 in the United States, Israel and Germany.

That scarcity of evidence is itself diagnostic. Eight of the nine studies focused on patients, five of them specifically on women with breast cancer, a condition supported by comparatively well-resourced care pathways. Only one study examined the perspective of healthcare professionals, and none at all explored the experiences of communication support professionals, the sign language interpreters, lip speakers and notetakers who mediate between d/Deaf patients and hearing clinicians. The researchers registered their protocol on the Open Science Framework and used the PCC framework, defining population, concept and context, to structure their questions around patient experiences, professional educational needs and the role of interpreters in cancer settings.

Thematic analysis of the included studies revealed three overarching domains of barriers: system-level, interpersonal and patient-level factors. At the system level, the most persistent problem was the simple absence of interpreters during consultations, including conversations in which a cancer diagnosis was being delivered. Patients described feelings of loneliness, isolation and frustration when left to decipher complex medical information without linguistic support. Even when interpreters were present, quality varied alarmingly. In one account, a discussion of high medical risk was rendered into American Sign Language as a phrase translating roughly as dangerous, dead, can, a misinterpretation the patient said directly altered their treatment decisions. Poorly designed consultation rooms that blocked sightlines to the interpreter, and patient portals that offered no way to request interpreting services, compounded the failures.

The interpersonal domain was equally troubling. Patients repeatedly reported that clinicians had limited understanding of d/Deaf culture and communication needs, falling back on lipreading or written notes, methods the review notes are often ineffective. Some healthcare professionals displayed impatience or reluctance to adapt, and a few held outright misconceptions, assuming that a patient who could lipread needed no interpreter, or that d/Deaf patients were illiterate. In one documented case, such an assumption nearly led to a patient being excluded from a clinical trial. In a survey embedded in one of the included studies, 87 percent of d/Deaf patients said clinicians spoke too quickly, 43 percent reported that eye contact was not maintained, and 85 percent said face masks obscured the facial expressions that carry so much meaning in signed and lipread communication.

The consequences of these failures are measurable and serious. Evidence cited in the review shows that 64 percent of d/Deaf patients with prostate cancer are diagnosed at an advanced or metastatic stage, compared with 13 percent in the general population. Half of d/Deaf men surveyed lacked basic knowledge of prostate cancer, and 37 percent reported receiving no information about early detection or prevention. Among d/Deaf women, 35.8 percent held misconceptions about the purpose of mammograms. A large English study of more than 473,000 women found that those with recognised disabilities, including d/Deaf women, were significantly less likely to participate in breast cancer screening, with a relative risk of 0.64, and in bowel cancer screening, with a relative risk of 0.75.

At the patient level, the review documented gaps in health literacy that flow directly from inaccessible communication. Some breast cancer survivors interviewed in the included studies lacked a clear understanding of what cancer actually was and were uncertain about the procedures and medications they had received. Seventy-two percent of d/Deaf patients in one survey struggled to understand verbal instructions about medication and examinations. Over a third reported difficulty grasping the full scope of their treatment and making informed decisions during consent conversations. Beyond comprehension, the review found emotional consequences: distrust of clinicians, disengagement and avoidance of care. One patient told researchers they had become their own doctor, doing their own research because they no longer believed what clinicians told them.

The single study examining healthcare professionals offered a counterpoint of cautious optimism. Clinicians who worked with interpreter teams reported improved communication and better patient assessment, and one described the sobering discovery that a patient had no idea they had cancer until a consultation was finally conducted through an interpreter in American Sign Language. The review also highlights the potential of Certified Deaf Interpreters, deaf professionals whose cultural knowledge and lived experience allow them to work alongside hearing interpreters using gestures, mime and visual props, particularly in complex medical appointments. Yet the authors note that such specialists were entirely absent from the literature they reviewed, and that many d/Deaf patients have no access to any interpreter, or are assisted by someone without adequate medical training.

The review’s authors are careful about the limits of their evidence. The included studies were small, largely exploratory and disproportionately focused on breast cancer in the United States, which accounted for 78 percent of the literature. All were published in English, and deaf community members were rarely involved in designing or interpreting the underlying research. Even so, the converging picture supports concrete interventions: reliable access to qualified medical interpreters, visually based educational materials in sign language, and deaf awareness training for healthcare staff. Educational programs delivered in sign language have already improved knowledge of prostate, breast and cervical cancer screening, with retention lasting up to two months, and cultural competency programs such as the Deaf Strong Hospital exercise have measurably improved medical students’ communication. Targeted cancer-specific training for medical interpreters has been associated with a 23 percent improvement in cancer knowledge, a model the authors argue should be extended to communication support professionals, whose educational needs a survey now underway aims to define.

What makes this review resonate beyond oncology is its alignment with the social model of disability, which locates the problem not in deafness itself but in systems that fail to accommodate it. The barriers documented here, missing interpreters, rushed speech, obscured faces, inaccessible portals, are all artifacts of design and policy, not of biology. As cancer diagnosis and treatment grow more complex, the communication demands placed on every patient increase, and for d/Deaf patients the margin for misunderstanding narrows to nothing. The review’s nine studies may be a small foundation, but they point in a clear direction: equitable cancer care for d/Deaf people is not a question of new medical technology, but of whether the healthcare system is finally willing to learn their language.

Subject of Research: Communication barriers experienced by d/Deaf patients in cancer care

Article Title: Communication barriers for d/Deaf people with cancer: a scoping review

Article References: Wogan, N., Habibi, R., Fallowfield, L., & Harder, H. (2026). Communication barriers for d/Deaf people with cancer: a scoping review. Supportive Care in Cancer, 34(10), Article 950. https://doi.org/10.1007/s00520-026-11202-y

Image Credits: AI Generated

DOI: 10.1007/s00520-026-11202-y

Keywords: d/Deaf, cancer care, communication barriers, sign language interpreters, health literacy, scoping review, health inequalities, oncology, deaf awareness training, patient-provider communication, supportive care, health services research