Background: Psychological recidivism-reducing interventions with serious, young violent offenders in residential care have unsatisfactory effects. We tested if a complementary individual cognitive behavioral therapy (iCBT) intervention focusing problem-solving, cognitive self-control, and relapse prevention reduces criminal recidivism beyond usual institutional care encompassing interventions such as social skills training and prosocial modeling .Method: We consecutively approached 115 eligible serious, male violent crime offenders in five residential treatment homes run by the Swedish National Board of Institutional Care. Eighty-one (70%) 16 to 21-year-old youth at medium-high violent recidivism risk were included and randomized to an individualized 15 to 20-session CBT intervention plus TAU (n = 38) or to TAU-only (n = 43), 4–6 months before release to the community. Participants were assessed pre- and post-treatment, at 12 months  and 24 months (reconvictions) after release. Intent-to-treat analyses were applied.Results: The violent reconviction rate was slightly higher for iCBT+TAU vs. TAU-only youth at 12 months  and 24 months following release , but neither of these differences were significant. Cox regression modeling also suggested non-significantly, negligibly to slightly more violent, and any criminal recidivism in iCBT+TAU vs. TAU-only youth during the entire follow-up. Further, we found no significant between-group differences in conduct problems, aggression, and antisocial cognitions, although both iCBT+TAU and TAU-only participants reported small to large within-group reductions across outcome measures at post-treatment. Finally, the 12-month follow-up suggested marginally more DSM-5 Conduct Disorder (CD) symptoms of “aggression to people and animals” in iCBT+TAU vs. TAU-only youth  although this difference was not significant.Conclusion: We found no additive effect of individual CBT beyond group-based TAU in residential psychological treatment for serious, young male violent offenders. Limited sample size and substantial treatment dropout reduced the robustness of intent-to-treat effect estimates. We discuss the possible impact of treatment dose and integrity, participant retention, and TAU quality. Interpersonal violence is a profound global social and public health problem. For instance, the World Health Organization (WHO) concludes that homicide is the third leading cause of death internationally for 15 to 44-year-old males  whereas contagion effects suggest a need for individualized interventions to complement the more common group-based interventions in juvenile forensic institutions  for cognitive behavioral and multimodal interventions. Compared to control groups, Koehler et al. . Specifically, CBT-interventions had a moderate effect (d = 0.50) based on a summary measure containing delinquency, behavior problems, skills, and a miscellaneous problem category.Although treatment effects tend to be small, systematic reviews have suggested promising treatments to reduce criminal recidivism e.g., , 15]. Re. Re15)].r et al.  found CBr et al.  comparedindividualized CBT components could be more effective in reducing severe aggressive behavior in adolescents compared to regular care or treatment-as-usual (TAU) with no CBT components (between group d = 1.14). The authors conclude that the addition of individually tailored interventions based on the risk, needs, and responsivity (RNR) principles  added to standard group-based treatment (TAU) in reducing reoffending, compared to TAU alone. Specifically, our hypothesis was that iCBT+TAU would reduce self-reported conduct problems, aggression, and antisocial cognitions as well as criminal recidivism more than TAU-only.We conducted a randomized, controlled trial in Sweden across five (out of the six existing) residential facilities for serious young violent offenders sentenced by general criminal courts to secure care according to the Closed Institutional Youth Care Act. The secure facilities, administered by the National Board of Institutional Care, are located across Sweden and participant inclusion occurred between December 2003 and August 2006. Sweden has no formal separation of juvenile and adult justice systems and Closed Institutional Youth Care was introduced on January 1, 1999, as a new sentence for adolescents between 15  and 17 years guilty of serious criminal offenses. Crime categories usually include (aggravated) robbery or assault, homicide or rape. Closed Institutional Youth Care was introduced as a custodial replacement to imprisonment with adults in the general prison system. Sentence lengths vary from 14 days to 48 months, the full term is served in an institution and there is no parole. During 2000–2006, when the youth in this study were convicted, 115–120 individuals yearly  were convicted to an average of 9 months in secure care according to the Closed Institutional Youth Care Act .We included young male offenders with 4–6 months remaining of an ongoing residential youth care sentence of ≥6 months for a non-sexual, violent crime. We defined violent offenses as homicide, assault, assault of an officer, robbery, and aggravated arson while sexual offenses were not included. Attempted or aggravated versions of these offenses were included whenever applicable. Female offenders were not included due to very small numbers overall and placement in non-participating residential facilities. Youth were ineligible to participate if they did not speak Swedish sufficiently well or had current severe, destabilizing psychiatric disorders involving psychotic or suicidal features.Twenty-one youth were lost from possible participation prior to being asked. Eleven of these were either moved to a non-participating institution or available psychotherapist(s) had no room at the time to take them on for iCBT following possible inclusion. Another ten individuals were not asked due to miscommunication between researchers and staff at the five participating institutions. Finally, four youth were not approached due to intellectual impairment  as ascertained from psychological testing or a psychiatrist or psychologist's clinical judgment.M = 17.7, SD = 0.9) were moderately younger than non-participants . The proportion of youth that consented to inclusion ranged from 67% (18/27) to 74% (17/23) across the five residential treatment homes. The average sentence length for participating youth was 10.2 months . Since one male was mistakenly asked to participate just before release, 81 subjects were randomized either to TAU+iCBT (n = 38) or TAU-only (n = 43); the difference in numbers was due to chance.A total of 115 eligible male youth were asked for possible inclusion, 82 of which (71.3%) agreed to participate following oral and written informed consent see . Main sen = 20) were non-immigrants with majority ethnicity, defined as being born in Sweden with both biological parents born in Sweden. Forty-six percent  were first-generation immigrants, born abroad and with both parents born abroad. Thirty percent (n = 24) were second-generation immigrants, born in Sweden with one or both parents born abroad. For further details, see Participants were all males aged 16–21 years at inclusion. Twenty-five percent . Eligible young violent offenders at the five participating residential treatment facilities were consecutively asked to participate by a psychotherapist or another staff member, usually the head of the ward. Subjects provided oral and written informed consent to participate. For participants younger than 18 years, oral and written permission were also obtained from his legal guardian. At baseline, the youth completed six self-report questionnaires (described below) provided by the staff at the residential facilities. Participants were informed that all information they provided during baseline assessments and throughout the study was for research only and would not be accessible for ward and clinical staff. The youth were given as much time they needed for the completion of the questionnaires and instructed to ask a nearby staff member for help in case of difficulty to read or understand items. The staff made sure that the youth completed the questionnaires on his own, with no other youth disturbing him. Each participant personally put his filled-out questionnaires in an envelope and sealed it followed by the envelope being collected by the research assistant. Within a week from the completion of the questionnaires, the youth was interviewed and assessed face-to-face with the SAVRY and the PCL:SV by a trained research assistant (B.Sc. in psychology and criminology). The research assistant was not involved in youth care and all participants were again carefully informed that no information provided during assessments would be revealed to ward staff. We also explicitly informed about the only exception to this: a duty to report to the social services  if the youth would reveal information about any specific, named child currently at imminent risk of suffering harm, including child abuse or neglect. No such reporting was deemed necessary during the trial.Participants received 100 SEK (approximately 10.50 USD) for completion of self-report questionnaires and participation in the baseline interview. One to three weeks before leaving the institution, the youth completed post-treatment questionnaires, again administered by the staff. Again, we reminded participants that all information was for research only and would not be used against them. Subjects received another 100 SEK upon completion of the post-treatment assessment.Participants were randomized to either iCBT plus the standard intervention (TAU) (experiment group) or TAU-only (control group) across all five sites to reduce the risk of bias due to intervention differences between units. Randomization was obtained with a pre-existing, computer-generated series in an unweighted fashion with either “iCBT” or “TAU” printed on paper at an overall 1:1 ratio. Every single printout was individually placed in opaque envelopes held centrally by the research group and later drawn by the last author when contacted by the research assistant or a site coordinator reporting that a specific eligible youth had completed pre-trial assessments.Psychology of criminal conduct provided important inspiration for the program, particularly regarding adherence to the RNR principles of effective rehabilitation. These principles suggest that effective treatments against antisocial behavior should focus on offenders with higher recidivism risk, target criminogenic needs that drives criminal behavior, and address individual learning styles as well as resources and barriers within and around the individual offender responsivity   is a manonsivity .Social learning and cognitive behavioral theories and methods as well as treatment philosophy were described in detail in Lardén , that waAn individual case formulation based on identified criminogenic needs was conducted at the start of the intervention. The case formulation contained a description of the adolescent's criminal history focusing on both the index offense and prior antisocial development. First, five criminogenic need domains related to recidivism risk  were mapFor the iCBT group, the intervention was added to ordinary treatment curricula at participating institutions, while controls received solely the ordinary curricula (TAU). Seven therapists (4 men and 3 women) were recruited from the treatment staff at participating institutions . Three were board-certified clinical psychologists, two academic social workers, and two were staff with a general education and specific training in individual psychotherapy. All, except one psychologist, had more than 10 years' experience of clinical work with serious young offenders. All therapists/iCBT providers attended an initial 2-day iCBT training seminar. Treatment integrity was upheld through repeated, individual supervision by e-mail up to once per month and through 1- or 2-day meetings twice a year.Treatment-as-usual consisted of ordinary residential treatment interventions at the five participating institutions; the specific contents varied across sites. Most of the time in residential homes was spent on structured activities of daily living, formal education, and leisure activities. The most common active intervention was interpersonal skills training sessions based on Aggression Replacement Training (ART)  with up Youth Self-Report (YSR)   is a 111validity , 32. Thevalidity ]. We useReactive and proactive aggression scale  and items are added in a linear and unweighted fashion to subscale summary scores. The zero-order correlation between the 10-item proactive and 6-item reactive aggression scales was high in the original version (r = 0.70). Internal consistency was also high . In this study, internal consistency was high for the total and proactive scales , but weaker for the reactive scale (α = 0.57). We used the total score, as well as proactive and reactive aggression subscales for baseline and post-treatment assessments.We used a self-report version of the on scale  tapping How I Think (HIT)  where high scores indicate more cognitive distortions. Internal consistency expressed as Cronbach's α was 0.94 in this study, compared to 0.96 in a previous Swedish report with adolescents as well as for the original English version (nk (HIT)  is a 54- version , 36.Sociomoral Reflections Measure—Short Form (SRM-SF)   is a selin youth –39, inclin youth , expressin youth . The Swein youth . For theThe Structured Assessment of Violence Risk in Youth (SAVRY) (low (0), medium (1), or high (2) while protective factors were coded dichotomously as present (1) or not (0). SAVRY was translated into Swedish by the last author following the North American original as closely as possible and yet being sensitive to Swedish social and legal conditions. We made a minor adjustment regarding the final professional judgment of future violence risk by excluding sexual crime from recidivism that the rater should aim at predicting, as risk factors for sexual reoffending in adolescents are partly different from those covered by SAVRY ( (SAVRY)  is a risby SAVRY –45. We snot present (0), partly/maybe present (1), or definitely present (2). Inter-rater reliability, again measured across 25 individuals, was high (single rater ICC = 0.81) for PCL:SV total scores and interpersonal/affective and unstable lifestyle/antisocial factors had interrater reliability scores of 0.81 and 0.68, respectively. Whether violent offenders with many psychopathic personality traits are truly treatable has been an important question in correctional and forensic practice . Alt. Altnot n = 43), we used the highest reported value. The outcome score was based on an unweighted summary of the sevennever, 1–2 times, 3–5 times, 6–10 times, and 11+ times) regarding the past 12 months . We recoded answers into a three-point scale:  resulting in a possible score range of 0–16. Aggressive CD symptom data were provided by 64 of the 81 participants (79%). Ten iCBT participants and seven TAU-only controls were unavailable for this outcome.Aggressive behavior at 12-month follow-up was measured as a conduct disorder (CD) symptom summary score derived from structured questions in follow-up telephone interviews with each participant's social service case manager, the youth himself, or both. The interviewing research assistant was masked to the youth's prior residential treatment allocation (iCBT+TAU or TAU-only) and participants and social service case managers were explicitly instructed at the beginning of the interview to not tell the interviewer details about prior residential treatment. We obtained interpretable data from 58 youth interviews and 49 interviews with social service staff. When both sources were available , small (0.20–0.49), moderate (0.50–0.79), or large (0.80+) effects. Pre- to post-test comparisons were done variable-wise as paired t-tests that were translated into Cohen's d:s using the freely available effect size calculator provided by the Memorial University of Newfoundland, Canada . All statistical analyses were performed with the IBM Statistical Package for the Social Sciences (SPSS) version 24.For pre- to post-treatment changes across six outcomes , we usedBased on our reading of the literature when planning the study, we assumed a, in hindsight overly optimistic, difference in violent recidivism rates of 50 vs. 25% for iCBT+TAU over TAU-only. Before starting the study, we decided on a less conservative α of 0.10 in an attempt to balance risks for false positive findings (type I errors) and false negatives (type II errors). Reaching statistical significance at α = 0.10 (two-sided test) with a power of 0.80 would require 88 (44 treated and 44 control) participants.d = 0.21–0.47), significant (urban residence) and non-significant baseline differences  between youths randomized to iCBT+TAU or TAU-only. Except for somatic anxiety and index violent offense type, both empirically unlikely to be related to violent recidivism risk, five of these seven covariates were controlled for in the Cox regression model described below.F = 2.99, p < 0.10].Pre- to post-treatment reductions in self-reported conduct problems, aggression, and antisocial cognitions are presented in SD = 3.55, range 0–11). We found no significant difference in CD symptom scores between iCBT+TAU and TAU-only participants  as reported by the youth themselves or their social service case managers  and 24 months . Similarly, any reconviction differences at 12 and 24 months were marginal to small and non-significant.Violent reconviction rate differences were small but non-significantly higher for iCBT+TAU youth at 12 months , and at 24 months .There were small-sized, non-significant differences in number of offense counts favoring TAU-only over iCBT+TAU youth at 12 months . Controlling for five small-sized covariate differences at baseline, iCBT+TAU compared to TAU-only participants had slightly, non-significantly higher risk of violent recidivism  and negligibly lower for any recidivism , respectively. Corresponding estimates for the initial, unadjusted Cox regression model were essentially the same (data not shown).We used Cox proportional hazards regression to compare recidivism rates for iCBT+TAU and TAU-only subjects for the entire follow-up period , and had substantially less ADHD symptoms  and oppositional defiant symptoms than TAU youth . Finally, iCBT completers had moderately but non-significantly more SAVRY protective factors compared to TAU-only youth . There were no other meaningful differences between iCBT completers and TAU-only youth on the remaining baseline measures.Despite the best efforts of the contributing therapists and their supervisor, only 15 of 38 youths (39%) randomized to iCBT finished enough sessions (15 or more) to be considered completers. Regarding baseline characteristics likely to affect treatment adherence, iCBT completers were moderately but non-significantly older than TAU-only youth (n = 3) of completing iCBT participants vs. 23% (n = 10) of TAU-only youth recidivated in a violent crime within 12 months . Corresponding figures for any crime within 12 months was 60% for iCBT completers (n = 9) and 65% (n = 28) for TAU-only participants . At 24 months, 33% (n = 5) of iCBT completers vs. 40% (n = 17) of TAU-only participants had been reconvicted for a violent crime . Correspondingly, within 24 months, 53% (n = 9) of iCBT completers and 74% (n = 32) of TAU-only participants had recidivated in any crime .Regarding criminal reconvictions, 20%  or any reconviction  when comparing iCBT completers with TAU-only participants.addition of an individualized CBT intervention to TAU. A nationwide consecutive sample of 81 youths were randomized to iCBT+TAU or TAU-only in a five-site ecological setting in Sweden. There were three main findings. First, we found substantial pre- to post-treatment improvements on self-reported conduct problems, aggression scores and antisocial cognitions for both iCBT+TAU and TAU-only youth, but no meaningful differences between treatment arms. Second, in intent-to-treat analyses, we were unable to statistically ascertain risk-reducing effects of iCBT treatment on aggression scores at 12 months or on registered reconvictions in violent or any crime at fixed 12- and 24-month follow-ups. Neither did we find any risk-reductions effects of iCBT when looking at the full follow-up period, or on number of conviction counts at 12- and 24-months following release to the community. Third, although complementary per-protocol analyses suggested negligible to small effects favoring iCBT completers over TAU youth, these comparisons were also non-significant.Concerned by the limited support for the effectiveness of available group-based psychological interventions in residential care for serious violent young offenders, we investigated the potential effectiveness of the We conclude that an individualized CBT intervention for medium-to-high risk young male violent offenders in residential treatment, focusing on cognitive self-control, and relapse prevention, was insufficient to reduce aggression and criminal reconvictions over and above group-based TAU treatments. iCBT included components known to be associated with positive outcomes, including relapse prevention, focus on interpersonal skills, and homework assignments e.g., , 55], bu, bu55)],Potentially effective pharmacological treatment with central stimulants for ADHD, mood stabilizers, and medications against drug craving are substantially more common in residential care today than in 2003–2006. Unless considered in study design and analyses, their use may complicate inferences about possible effects of psychological interventions, for example by leveling out the outcomes of experimental and control groups. Although other studies reveal small possible changes in the prevalence of substantial psychiatric (co)morbidities over time , we areTAU variability ]ffenders . Notablytreatment integrity could be a limitation also in this study. Contributing iCBT therapists were expected to participate in repeated supervision in person and by email and were encouraged to contact the supervisor whenever needed. However, perhaps inevitably with high-risk serious violent youth clients, some of them experienced difficulties with adhering to the treatment process. Based on the suggested non-significant trend toward marginal or small positive effects for iCBT completers compared to TAU-only controls, treatment non-completion may have influenced overall results.Second, systematic reviews of treatment of young offenders suggest that effectiveness studies  more often suffer from attrition, insufficient descriptions of implementation or poor quality of the latter than do efficacy studies. Sustatistical power is important to avoid random errors due to data variability , well-pmartin.larden@kriminalvarden.se.The dataset presented in this article is not readily available since it contains sensitive details about the participants. Requests to access the dataset should be directed to Martin Lardén, The study was reviewed and approved by the Regional Ethics Review Board in Stockholm, Sweden. Written informed consent to participate was provided by the youth himself and, for participants younger than 18 years, also from parent(s)/legal guardians.ML and NL designed the study. ML coordinated the data collection, conducted the data analyses, and drafted the initial manuscript. All authors reviewed the manuscript for important intellectual content and helped shape interpretations and the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. ML designed the CBT intervention, but has not made economic or other gains from royalties, training, or consulting regarding the model.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


People with chronic conditions are disproportionately prone to be affected by the COVID-19 pandemic but there are limited data documenting this. We aimed to assess the health, psychosocial and economic impacts of the COVID-19 pandemic on people with chronic conditions in India.n = 2335) with chronic conditions across four sites in India. Data on participants’ demographic, socio-economic status, comorbidities, access to health care, treatment satisfaction, self-care behaviors, employment, and income were collected using pre-tested questionnaires. We performed multivariable logistic regression analysis to examine the factors associated with difficulty in accessing medicines and worsening of diabetes or hypertension symptoms. Further, a diverse sample of 40 participants completed qualitative interviews that focused on eliciting patient’s experiences during the COVID-19 lockdowns and data analyzed using thematic analysis.Between July 29, to September 12, 2020, we telephonically surveyed adults . The mean (SD) age of respondents was 57.8 years (11.3) and 50% were men. During the COVID-19 lockdowns in India, 83% of participants reported difficulty in accessing healthcare, 17% faced difficulties in accessing medicines, 59% reported loss of income, 38% lost jobs, and 28% reduced fruit and vegetable consumption. In the final-adjusted regression model, rural residence , having diabetes  and hypertension , and loss of income  were significantly associated with difficulty in accessing medicines. Further, difficulties in accessing medicines , and job loss  were associated with worsening of diabetes or hypertension symptoms. Qualitative data suggest most participants experienced psychosocial distress due to loss of job or income and had difficulties in accessing in-patient services.People with chronic conditions, particularly among poor, rural, and marginalized populations, have experienced difficulties in accessing healthcare and been severely affected both socially and financially by the COVID-19 pandemic.The online version contains supplementary material available at 10.1186/s12889-021-10708-w. As the global burden of novel coronavirus disease 2019 (COVID-19) continues to increase, particularly in low- and middle- income countries such as India, it imposes huge costs on individuals, communities, health systems, and economies . People As of March 11, 2021 more than 11 million people in India had been infected with COVID-19, and about 158,000 had died . The sprMeasures to address coronavirus spread including lockdowns may have serious economic consequences and unintended effect of exacerbating rather than mitigating health disparities , 23, 24.We conducted a cross-sectional study using sequential mixed methods design, comprising a quantitative survey and qualitative interviews to describe the impact of COVID-19 on the health, psychosocial, and economic well-being of people with chronic conditions in India. Adults with one or more chronic conditions , from the two large existing cohorts  reasons, and treatment satisfaction. Quantitative survey questionnaire and qualitative study interview guide were developed by the authors for this mixed-methods study . ParticiWe used a sequential mixed methods study design to guide our analytical approach , 30. DatQualitative data analyses focused on identifying views of individuals with chronic conditions, as well as the context, challenges, and mitigating factors or efforts to better manage chronic conditions during the COVID-19 pandemic in India. In-depth interviews with participants were audio-recorded, transcribed (verbatim), translated, anonymized, and checked for accuracy. The interview transcripts were coded thematically using MAXQDA software version 2020 . InitialOverall, 1734 out of 2335 contacted participants (74.3% response rate) completed the survey. We found 58 cohort members (2.5%) had died, 34 (1.5%) refused to participate, and 509 (22%) were not reachable for various reasons. Mean age (SD) of respondents was 57.8 (11.3) years, 50% were men, a majority had secondary school or college level education, and one-quarter of participants reported monthly household income of >INR 30,000 , 95% confidence interval (CI): 4.01,2.90–5.53), having diabetes  and hypertension , and loss of income  were significantly associated with difficulty in accessing medicines. Financial aid from the government reduced the odds of difficulty in accessing medicines, i.e., had protective effect  Fig. . Figure One-third of respondents did not adhere to their recommended diet plan and reduced fruit and vegetable consumption during the lockdowns Table . About tBecause of the pandemic and related restrictions imposed to reduce its spread, few participants (15.2%) reported visiting friends/family, although about half were able to leave their locality to buy food or other supplies (52.6%). The majority reported that fruits, vegetables, and essential groceries were available during the lockdowns (96.8%), although we do not know prices or quality. Most participants (99.4%) reported being aware of and following recommended preventive measures such as wearing mask, handwashing, and social distancing (online Table N = 40) to confirm thematic redundancy. Interviews lasted about 20–40 min. Two major themes emerged from qualitative data analysis: “challenges faced”, and “resilience and mitigating factors”.Our sample consisted of 40 participants with one or more chronic conditions, mean age: 54.6 years, and 64% were men. Thematic redundancy was achieved with 8th interview, and two participants were then interviewed from each of the four sites “The impact was that there were a lot of problems. We took the ration distributed by the government. We consumed that. There were a few things [at home], we sold one or two things with the help of my daughter. My son drives a rickshaw, and my husband stays at home; we are old. It impacted him [spouse]. He was out of work for three months.” (U-10-D)Some participants had difficulty accessing inpatient services, since many hospitals were full or refused new admissions due to COVID-19 cases. Many participants were concerned about visiting the hospital or doctor and delayed testing of their blood sugar because of fear and anxiety about COVID-19.“I was not keeping well and none of the hospitals were taking any admission . . . they [hospital staff] said that due to COVID, beds are not available. And if you are ready to sleep on ground then we will take your admission.” (U-08-V)“I was scared that I may not have this [coronavirus infection] but because of someone else I may get affected. We have doubt to go to the hospital, to the doctor. I didn’t want to get infected by this (COVID-19).” (U-02-D)Participants with diabetes and hypertension were almost all aware of their elevated risk of poor outcomes if infected with SARS-CoV-2 and many feared to go out for a walk or other regular exercise.Most participants faced financial difficulties during the COVID-19 lockdowns. Several participants reported difficulty getting to work because of lack of public transportation. Some participants lost their jobs due to the COVID-19 pandemic, as reflected in the following quotes from study participants:“We have to be careful from the corona and we have to be safe from this. That’s the only medicine now.” (U-01-D)Participants were well informed and emphasized the importance of wearing masks, practicing social distancing, or handwashing. Few participants utilized teleconsultations with doctors to avoid making in-person clinic visits. Most participants embraced the practice of enhanced personal cleanliness and other measures to proactively reduce risks of COVID-19 infection and transmission.COVID-19 pandemic related restrictions implemented to control it had unforeseen adverse impacts on the health status, access to treatment, and achievement of care goals among people with chronic conditions in India. We found rural participants disproportionately experienced acute medical illnesses; difficulties in accessing healthcare; relatively less availability of functioning health facilities; poor treatment satisfaction; and reduced fruit and vegetable consumption.Infectious disease epidemics have tended to have spillover effects onto the wider economy , 33–37. Our study results are consistent with other online surveys conducted among people with chronic conditions and healthcare providers that showed the coronavirus pandemic and its related lockdowns significantly reduced access to healthcare, adversely impacted self-care behaviors, and increased mental health problems , 24, 38.The COVID-19 pandemic is unprecedented and serious, and several of the policy measures taken to mitigate and contain it were necessary and understandable. At the same time, we believe that the data from our study provide insights for policy makers as they consider the asymmetrical psycho-social and economic impacts of the pandemic on people with chronic conditions, especially underprivileged urban residents and underserved rural communities. In our study, rural residents and those of lower educational attainment experienced more difficulties in accessing medicines, controlling for other demographics and self-reported income. Difficulty in access to medicines, in turn was associated with worsening of diabetes or hypertension symptoms. Global supply chain disruptions during the pandemic contributed to reported shortages of essential medicines for chronic conditions . FurtherOur data may assist health authorities to redesign care delivery models to address the urgent needs of people with chronic conditions. We recommend a three-pronged approach to design resilient healthcare systems during and after the COVID-19 pandemic: a) develop and implement digital campaigns to disseminate information on how to adopt healthy behaviors, better self-manage NCDs, and control COVID-19; b) decentralize healthcare delivery for people with chronic conditions by involving trained community health workers and using technology-assisted medical interventions along with home monitoring devices to improve health care services; c) provide effective social and economic support for people with chronic conditions, particularly rural communities, elderly, and those with severe mental health problems. Many have experienced loss of livelihoods, isolation, stress, and anxiety during the pandemic; however, those with preexisting chronic conditions have often experienced compounding effects that exacerbate their illness . TherefoThe strength of this study lies in its empirical mixed methods study design and focus on people with chronic conditions from both urban and rural populations. It is the first such study from a populous country like India. However, future research is needed to evaluate the longer-run impact of the COVID-19 pandemic on healthcare access and health outcomes for those both with and without NCDs.This study has important limitations. First, the cross-sectional nature of this study limits the causal inferences between SES and chronic conditions and the COVID-19 pandemic related restrictions. Second, although the data are derived from a wide cross section of four sites, it cannot be construed as definitively representative of all urban and rural India. Third, because of the ongoing COVID-19 outbreak that we are studying, it was not possible to conduct the interviews in person; phone interviews may have limited the interpretation of qualitative data since they do not allow direct observation of participants’ expressions and body language.In response to the rapid spread of the COVID-19 pandemic and associated health system disruptions experienced in under-resourced and low-income settings, there needs to be renewed focus on building resilient health systems that can deliver routine care using innovative telehealth approaches during the pandemic and respond to the shocks induced by infectious disease pandemics or other health crises effectively. People living in rural areas and underserved communities in urban areas faced greater challenges in access to healthcare and experienced worsening of diabetes or hypertension symptoms, as well as significant losses of income and employment. The pandemic exposed disparities in chronic disease management, but also provides opportunities to close gaps with innovations in the new post-COVID India.Additional file 1: Table S1. Factors associated with difficulty in accessing medicines during the COVID-19 lockdowns in India. Table S2. Factors associated with worsening of diabetes or hypertension symptoms during the COVID-19 lockdowns in India. Table S3. COVID-19 pandemic-related restrictions and preventive measures.Additional file 2. Supplementary file.


Retinitis pigmentosa (RP) is a rare, progressive disease that affects photoreceptors and retinal pigment epithelial (RPE) cells with blindness as a final outcome. Despite high medical and social impact, there is currently no therapeutic options to slow down the progression of or cure the disease. The development of effective therapies was largely hindered by high genetic heterogeneity, inaccessible disease tissue, and unfaithful model organisms. The fact that components of ubiquitously expressed splicing factors lead to the retina-specific disease is an additional intriguing question. Herein, we sought to correlate the retinal cell-type-specific disease phenotype with the splicing profile shown by a patient with autosomal recessive RP, caused by a mutation in pre-mRNA splicing factor 8 (PRPF8). In order to get insight into the role of PRPF8 in homeostasis and disease, we capitalize on the ability to generate patient-specific RPE cells and reveal differentially expressed genes unique to RPE cells. We found that spliceosomal complex and ribosomal functions are crucial in determining cell-type specificity through differential expression and alternative splicing (AS) and that PRPF8 mutation causes global changes in splice site selection and exon inclusion that particularly affect genes involved in these cellular functions. This finding corroborates the hypothesis that retinal tissue identity is conferred by a specific splicing program and identifies retinal AS events as a framework toward the design of novel therapeutic opportunities. Mutations in splicing proteins are described to account altogether as a second most common cause of autosomal dominant RP (adRP) (Retinitis pigmentosa (RP), the most common form of hereditary retinal dystrophies, is a progressive blinding disease that currently lacks effective therapies . TypicalP (adRP) .Splicing reaction is a process of excision of non-coding intervening sequences, introns, and exon ligations resulting in coding capacity diversification of a limited number of expressed genes with > 90% of 20,000 human protein-coding genes producing multiple mRNA isoforms. This stepwise reaction is performed by spliceosome, a multisubunit ribonucleoprotein complex with the core components uridine-rich small non-coding nuclear RNAs  and associated proteins that assemble on pre-mRNA to catalyze the excision of introns . MutatioPRPF mutations might cause global splicing dysregulation and affects only retina because of retinal enhanced splicing activity  from accessible tissue like patient’s skin, and coaxing them toward retinal tissue, offers an unprecedented opportunity to study the disease and also find new therapies. Moreover, the advantage of the iPSC-based models is that they recapitulate the disease-causing mutation and patient’s genetic complexity, essential for complex and late-onset diseases. The iPSCs can be directed toward both photoreceptors and RPE cells, capturing their morphology and function  and haved intact . These md intact . Finallyd intact . The afoPRPF8 (NM_006445:c.6974_6994del) (Patient-RPE) and patient’s non-affected tissue, i.e., fibroblasts (from here on: Patient-fibroblasts). An unrelated, non-affected individual was used as control (from here on: Control-RPE and Control-fibroblasts). We generated RNA sequencing (RNA-Seq) data for three independent experimental replicates per sample and performed a whole-transcriptome analysis where healthy control samples were compared to mutation-bearing cells, in order to depict retinal-specific transcriptional signature caused by the mutation.Herein, we have generated RPE cells from reprogrammed dermal skin fibroblasts derived from a patient diagnosed with adRP and bearing a pathogenic mutation in 6994del)  in a hetResearch procedures followed the principles of the Declaration of Helsinki. The study was approved by the Research Ethical Committee of the Hospital of Terrassa and Valencian Ethics Committee CAEC (Comité Etico Autonomico de Estudios Clínicos), Valencia, Spain. Both subjects provided written informed consent after the nature of the study procedures had been fully explained.The patient reported a history of nyctalopia starting from the first decade of life. At the age of 20 the best-corrected visual acuity (BCVA) was 20/40 in the right eye and 20/30 in the left eye. Anterior segment examination showed minimal posterior subcapsular cataract in the right eye, being normal in the left eye. Fundus examination showed the typical RP changes, consisting in optic disk pallor, retinal vessel attenuation, and extensive bone spicule-like pigmentation extending from the vascular arcades toward the periphery. No abnormalities at the macula were detected. Humphrey visual field examination showed a severe visual field loss, with 10° central preserved and a peripheral remnant in the left eye. Electroretinography was abolished at that time.At the age of 47, lens surgery had been performed in the right eye, so that BCVA was 20/40. In the right eye, she presented a moderate subcapsular cataract, being the BCVA 20/70. Fundus examination showed the typical RP changes. Spectral domain optical coherence tomography showed a complete absence of outer retinal bands corresponding to photoreceptors. Macular edema or epiretinal membrane was not detected in any moment of evolution.2. Fibroblasts at passages 6–8 were used in this study. Samples were collected in triplicates, from independent cell cultures. Authentication of the fibroblast cell lines by microsatellite STR markers was performed to confirm the identity to the iPSC lines.Cryopreserved fibroblast cell lines derived from skin biopsies from the female RP patient (Patient-fibroblasts) and a healthy (BCVA40/40) man (Control-fibroblasts) were thawed and cultured in DMEM  at 37°C under 5% CO2. When the colonies reached confluency, they were lifted and cultured in suspension in the absence of bFGF until the dark patches appeared. The dark patches were excised, trypsinized, and plated on collagen type IV/LN-521 coated plastic cell culture dishes where they acquired the RPE morphology within 4–8 weeks. RPE-like cells were passed through a 70-μm cell strainer in order to reach a homogeneous, highly pigmented RPE-like monolayer with characteristic uniform polygonal cell morphology. The differentiation experiments were performed in triplicates for both genotypes (Patient-RPE and Control-RPE). The samples were collected from each differentiation experiment (n = 3) and RNA extraction was performed.Two iPSC lines were employed in this study . The iPSCells were fixed with 4% paraformaldehyde (PFA), washed twice in PBS, and placed in blocking solution  for 1 h at room temperature. Cells were then incubated overnight at 4°C with one of the following primary antibodies: anti-PRPF8 , rabbit anti-CRALBP , rabbit anti-ZO1 , and mouse anti-Na/K-ATPase . The following day, cells were washed three to five times in PBS and incubated with an appropriate secondary antibody . After secondary antibody incubation, nuclei were stained with 4′,6-diamidino-2-phenylindole, dihydrochloride (DAPI)  and washed three times in PBS. The coverslips were mounted using Vectashield Mounting Medium  and imaged on Leica confocal microscope SP8.t test. Results are expressed as the mean ± SD. Values of p < 0.05 were considered statistically significant.Bovine rod POS were obtained from InVision BioResources  and labeled with FITC. Phagocytosis assay was performed as described previously . Briefly® TurboTM Transfer Pack/Bio-Rad). Membranes were incubated in blocking buffer (5% non-fat dried milk diluted in TBS + 0.1% Tween) for 1 h at room temperature, washed three times in TBS + 0.1% Tween for 5 min, and incubated with primary antibody (PRPF8 Abcam ab79237) at 1:500 dilution in blocking buffer overnight at 4°C. Thereafter, blots were washed three times in TBS + 0.1% Tween and incubated with secondary HRP-conjugated antibody in blocking buffer for 45 min at RT. Blots were washed another five times and protein bands were visualized using SuperSignal West Pico PLUS (Thermo Scientific) on X-ray films. β-ACTIN  was used as a loading control. HiMark Prestained Protein Standard  was used as a molecular weight standard.Fibroblast cells were lysed in RIPA buffer (R0278 Sigma) containing a protease inhibitor cocktail (Roche), and total protein was quantified using a Bradford Reagent protein assay (B6916 Sigma-Aldrich). Protein lysates were denatured by 1X SDS Sample Buffer. The resulting samples were incubated at 95°C for 5 min. Protein samples (100 μg) were then separated on TGX Stain-FreeTM Gels (Bio-Rad) and electroblotted onto a PVDF membrane  for 2 h, washed with the same buffer, and then postfixed in 1% OsO4 in PB. After gradual dehydration in ethanol series, the pieces were embedded in EPON 812. Semithin and ultrathin sections were obtained in an ultramicrotome . After staining with lead citrate and uranil acetate, ultrathin sections were examined in a JEM-1400 Plus electron microscope .® fluorometer (Life Technologies). Libraries were sequenced on a HiSeq2500 (Illumina) to generate 60-base (sequencing batch 1) or 50-base (sequencing batch 2) single-end reads, to a mean depth of 100M reads/sample for one replicate for each condition (sequencing batch 1) and a mean depth of 20M reads/sample for the other two replicates (sequencing batch 2). FastQ files for each sample were obtained using CASAVA v1.8 software (Illumina).High-quality total RNA (RIN > 7) from three independent experimental replicates of Patient-RPE, Control-RPE, Patient-fibroblasts, and Control-fibroblasts was extracted by RNeasy mini kit  and quantified by Agilent 2100 Bioanalyser. Total RNA (200 ng) was used to generate barcoded RNA-Seq libraries using the NEBNext Ultra RNA Library preparation kit (New England Biolabs). First, poly A + RNA was purified using poly-T oligo-attached magnetic beads followed by fragmentation and first and second cDNA strand synthesis. Next, cDNA ends were repaired and adenylated. The NEBNext adaptor was then ligated, followed by uracil excision from the adaptor and PCR amplification. The size of the libraries was checked using the Agilent 2100 Bioanalyzer and the concentration was determined using the Qubit2. TruSeq Illumina adapters  were removed using cutadapat  dapters) . Then, tdapters) . Gene-ledapters)  (htseq-cdapters) .Gene-level counts were normalized using Trimmed Mean of M Values (TMM) . RNA-Seqp value <0.05—equivalent to NOISeq probability > 0.95—and log2FC ≥ 1) between all meaningful pairs of clinical conditions and cell types: (A) two within-cell type contrasts to compare clinical conditions for the same cell type, i.e., Control-Fibroblasts vs. Patient-Fibroblasts and Control-RPE vs. Patient-RPE; and (B) two within-condition contrasts to detect differences between cell types for the same clinical condition, i.e., Control-Fibroblasts vs. Control-RPE and Patient-Fibroblasts vs. Patient-RPE.Differential expression (DE) analysis was performed using NOISeqBio . Four coTo better interpret the DE results, we used the information in the control and fibroblast contrasts to filter the results of the patient and RPE contrasts, respectively. In particular, in the within-cell type contrasts, DE genes found in the Control-Fibroblasts vs. Patient-Fibroblasts that were common to the Control-RPE vs. Patient-RPE were removed from the latter list . Since fp value <0.05).Functional Enrichment analysis of these sets of DE genes was performed for Gene Ontology (GO) annotations  and several extracellular matrix-related terms   for the control comparison , chromosome segregation (GO:0007059), and kinetochore (GO:0000776)  and ribosome structure and translation   identified significant enrichment  of a broad set of biological functions related to cell division and the cytoskeletal elements participating in mitosis, including 0000776) . The fun0006614) . Ribosom0006614) .In order to shed light on the mutant PRPF8 pathomechanism, we analyzed splicing patterns in the different cell types and clinical conditions and we evaluated the difference in Percentage Spliced In  for each of the four contrasts , considep value <0.05) when comparing RPE cells from different clinical conditions than in the case of fibroblasts , including several alternatively spliced zinc finger genes , as well as ribosome (GO:0005840) and structural constituent of ribosome (GO:0003735), which included some genes also annotated for mitochondrial translation, i.e., Mitochondrial Ribosome Protein genes from the Large subunit (MRPL genes). In addition, several splicing-related terms were among the most frequently annotated  and catalytic step 2 spliceosome (GO:0071013). Genes under these annotations included PRPF4, PRPF8, and PRPF31, known to be involved in RP . Therefore, the PRPF8 mutation could have a dual role in altering both the expression and the splicing of other spliceosomal genes and, potentially, their function. Ultimately, we hypothesize that the RP disease would be caused by the cumulative effect of these alterations in the splicing machinery.We next performed a functional enrichment analysis of genes with at least one significant AS event, removing events common between the fibroblast and RPE contrasts as previously described for the DE analysis . Functional analysis of events unique to the RPE contrast showed no significantly overrepresented terms (FDR < 0.05). Hence, we ranked GO terms by their frequency of annotation in alternatively spliced genes to gain functional insight into the splicing patterns of the disease. The most frequently annotated GO terms were nnotated , namely,ed in RP , as wellnd SRRM2 . This suSRSF1 and PRPF4B, the latter involved in AS, contradicted this pattern and showed highly included IR events in Patient-RPE, together with a decrease in expression in this clinical condition. This deviation from the general pattern for SRSF1 and PRPF4B agrees with previous reports of increased intron retention in RP , which are known to participate in splicing control  in the patient contrast  and rRNA processing , two functional terms that appear linked to the PRPF8 mutation and RP throughout this study. These findings are in line with our hypothesis regarding the existence of a healthy splicing signature, involving spliceosome and ribosomal genes, that is required to maintain correct retinal function and is disrupted via splicing defects initiated with defective PRPF8. Another cell function that was shown to be enriched in genes DE in the control contrast , was the only common GO term among the most frequent annotations.We next used the dPSI values to look at event inclusion/exclusion patterns between cell types in each clinical condition . Regardicontrast , regulatrRNA processing genes  and an A3 event in patient (ITSN1). We consider these, together with genes presenting SE events , to be genes subject to strong post-transcriptional regulation and therefore candidates for future evaluation of the impact of these splicing changes on RPE function. Finally, among the 371 common events (significant in both contrasts), we found 14 events that presented different dPSI sign in the patient and control comparisons , while the exon becomes excluded in RPE in the patient contrast. This set of genes included HNRNPDL, associated with pre-mRNA processing. A similar trend is observed for A3 events in the CYB5D1 and TPM2 genes, as well as for an RI event in the SNORD locus .Genes annotated for parisons , i.e., aIn summary, after performing within-condition contrasts, we have observed a pattern of event inclusion in the control contrast that is lost in patient, when not completely reversed, as is the case of common genes. This mainly affects SE, A3, and A5 events for genes involved in splicing, rRNA processing, and proliferation. The role that the skipped exons or exon fragments play in the gene’s functionality is to be defined; however, our analyses suggest that the PRPF8 mutation creates this event exclusion pattern. We believe that these changes could alter the splicing signature required for healthy RPE identity and that they may be a consequence of AS dysregulation in the RP disease. Ultimately, this list of alternatively spliced events and genes should constitute a valuable resource for further validation in order to find candidates that can explain the PRPF8-mediated RP pathomechanism.Despite huge progress in the identification of genetic causes of the disease, the pathomechanism behind RP is largely unknown. While animal models have proven useful in many cases, albeit in the case of splicing factor-induced RP, they remain insufficient as the disease phenotype is poorly manifested. Moreover, the wide mutational landscape of splicing factor-caused RP is time- and cost-consuming to capture in animal models. In addition, studying disease-causing variants in genetic backgrounds that are demonstrably permissive of the disease is highly desirable in the case of splicing factor-induced RP due to high clinical diversity.We set out to explore the transcriptional landscape of patient non-affected and affected cells in order to elucidate the unique role of PRPF8 in its target cells, namely, RPE cells vs. non-retinal tissue. The use of iPSCs that can be differentiated toward any human tissue leverages the lack of access to native retinal tissue.Prpf8H2309P/H2309P mice, which showed reduced phagocytosis, possibly lies in the homozygous state of the causative mutation in the rodent model. The lack of morphological or protein marker expression differences between control and RP genotypes probably reflects the late-onset disease phenotype that emerges as a result of additional cumulative molecular events. It has been previously described that modeling late-onset diseases requires additional cellular insults, since reprogramming leads to erasure of age markers in the original fibroblasts  activity genes and extracellular matrix-related genes, some of the latter also showing changes in AS. GPCRs, the largest family of membrane proteins, act through ligand binding and are responsible for a wide variety of physiological roles. Extracellular matrix proteins are known to play a crucial role in supporting RPE cells in vitro . RPE synWithin-condition differential expression analysis  identified a set of common DE genes associated with mitosis-related processes and components. Importantly, control contrast-unique DE genes showed significant enrichment of splicing and ribosome structure and translation terms, while this signature was completely lost in the patient contrast. This suggests that splicing and ribosome-related processes could be important for cellular identity specification and that their expression dynamics is disrupted in PRPF8-caused RP. In this study, we propose two hypothesis that could explain this mechanism. First, the alterations in the expression of splicing-associated elements could propagate to ribosomal components and translation regulators that may require intervention of the spliceosome for their normal expression. Alternatively, RPE cells may display translational control mechanisms for sustaining RPE properties.Out of 90% AS genes in humans showing AS, it is estimated that 30% have tissue-specific isoforms . We set For alternative first and last exons, which are equivalent to Alternative Transcription Start and End Sites, inclusion was not globally favored in any of the conditions. This is not surprising, given that transcription start and end site choice is driven by the transcriptional machinery, instead of by the spliceosome, which operates after transcription is initiated, either post-transcriptionally or simultaneously to transcription . The lacIn sum, we identified 27 splicing-related genes, including PRPF8, with at least one differentially spliced event between Control-RPE and Patient-RPE. This result opens interesting possibilities regarding the role of PRPF8 as a splicing factor, regarding both autoregulation of AS of its own pre-mRNA and that of 26 additional splicing factors. In the context of the RP disease, PRPF8 may act as a master AS regulator in RPE cells, targeting a broad set of splicing-involved genes, leading to the propagation of defective PRPF8 function to the rest of the splicing machinery via splicing dysregulation. Similar results have already been described in literature, where the core splicing proteins were found to regulate RNA processing and RNA-binding factors . We hypoWithin-condition contrasts showed a higher number of significant AS changes in control over disease cells, similar to the DE results, indicating a depletion of spliceosomal function by PRPF8 mutation. For instance, there were 108 significantly changing intron retention events in the control vs. 20 in the disease contrast. In addition, functional enrichment results for control contrast AS genes identified splicing and ribosome-related functions within the top 10 most frequently annotated GO terms. These within-condition AS results corroborate splicing machinery disruption hypothesis as a potential mechanism for PRPF8-induced RP. Meanwhile, the only common term between control and disease cell types was regulation of cell proliferation, although different genes were identified as AS in each condition’s contrast. This finding is in line with previous reports where PRPF8 was found to affect mitotic cell cycle and RNA splicing GO terms after its depletion by siRNA . After rPrpf31+ /− retina and RPE were enriched for genes involved in mRNA processing. The iPSC-RPE from the PRPF31-affected patients exhibited a range of cellular defects, including loss of apico-basal polarity, altered pigment epithelium-derived factor (PEDF), and basal vascular endothelial growth factor (VEGF) secretion, barrier function, phagocytosis, and primary cilia deficiencies. These data are supportive of disrupted AS as a trigger of splicing deficiencies underlying specific biological processes. The observed splicing differences in our iPSC-RPE bearing a mutant PRPF8 copy points to a common primary pathogenic event. The fact that we did not observe morphological and functional disruptions in studied cells can be attributed to a unique PRPF8 mechanism. Another possibility is that our iPSC-RPE were insufficiently matured, which delayed the concomitant cellular events. In that regard, efforts for quantitative quality control to assess maturity instead of image-based analyses are emerging -selected RNA profiling described here precludes the involvement of other biologically relevant RNA species, such as microRNAs or long non-coding RNAs, which may also play a role in PRPF8-induced RP .The development of therapies for autosomal dominant retinal diseases with gain-of-function mutations involve strategies to inhibit expression of mutant protein and reduce the ratio of malfunctioned to wild-type protein. Along these lines, DNA oligonucleotides complementary to the pathogenic mRNA  or gene The datasets presented in this study can be found in online repositories. The names of the repository/repositories and access-ion number(s) can be found below: NCBI, GEO GSE165322.The studies involving human participants were reviewed and approved by CAEC Valencia. The patients/participants provided their written informed consent to participate in this study.ÁA-L: designed analysis pipeline, performed data analysis, interpreted results, and wrote the manuscript. HS: iPSC expansion and RPE production. AB-A: performed experiments and data analyses. VL: mutation analyses and interpretation. NC: TEM analyses. BD: clinical data. IH, BP, and MC: provided patient’s biopsy. JC, AB, and AD: library preparation and initial data analyses. SE: financial support. DL: overall concept and design, performed the experiments, manuscript writing, and financial support. All authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Research suggests that racial/ethnic disparities in COVID-19 in the US are largely driven by higher rates of exposure to SARS-CoV-2 among Hispanic/Latino and Black populations. Occupational exposures play a large role in structuring risk of exposure, and essential workers are at elevated risk of COVID-19 infection. At a national-level, workers categorized as “essential” and “high-risk” are disproportionately Hispanic/Latino, but we lack analysis examining local-level racial/ethnic disparities in potential occupational exposures. Using the 2015–2019 5-year American Community Survey, we estimated disparities between the proportion of US Born Hispanic/Latino, foreign-born Hispanic/Latino, and non-Hispanic white (NHW) essential or high-risk workers in 27 of the largest metropolitan areas in the country. We found that, on average, 66.3%, 69.9%, and 62.6% of US-born Hispanics, foreign-born Hispanics, and NHW, respectively, are essential workers, while 50.7%, 49.9%, 49.5% are high exposure risk workers, respectively. The median absolute difference in proportions of US born Hispanic/Latino and NHW essential workers was 4.2%, and between foreign-born Hispanic/Latino and NHW essential workers was 7.5%, but these disparities varied widely by city. High likelihood of occupational transmission may help explain disparities in COVID-19 infection and mortality for Hispanic/Latino populations, especially foreign-born, and may also help explain heterogeneity in the magnitude of these disparities, with relevance for other acute infectious respiratory illnesses spread in the workplace. •Occupational exposures play a key role in exposure risk for COVID-19.•We find wide disparities in the proportion foreign and US born Hispanic vs non-Hispanic Whites in essential and high exposure risk occupations.•Occupational disparities vary substantially by metropolitan area and may help explain differences in COVID-19 disparities by local area. Black, Occupational exposures are a key driver of disparities in SARS-COV-2 exposure, though risk of exposure differs by occupation. In particular, essential workers are at elevated risk of exposure while working because they often cannot work from home, work in crowded and poorly ventilated conditions, and have direct exposure to the public . In the Essential workers are workers in occupations deemed eligible to continue working by the Department of Homeland Security during state and local “stay-at-home” and “shelter-in-place” mandates, while high-exposure risk workers are workers in occupations that regularly involve risk of exposure to infectious disease. At a national level, Hispanic/Latino, other racial/ethnic minorities, and immigrants, are disproportionately represented among essential workers  and amonWe specifically focus on Hispanic/Latinos because of research suggesting that they have had among the highest rates of COVID-19 infection and death , though We employ racial capitalism theory to help explain racial/ethnic occupational disparities, and how structural factors pattern differential occupational exposures to infectious disease . Racial The objective of this paper is to conduct a descriptive analysis that categorizes occupational codes by high-exposure risk and essential worker category, and then examines racial/ethnic distribution of workers in these occupational groups, across major US metropolitan statistical areas (MSAs). We hypothesized that across all MSAs, foreign-born Hispanic/Latino workers would be most likely to work in essential and high-exposure jobs, followed by US born Hispanic/Latino and NHW workers.22.1The unit of analysis of this study were the 27 metropolitan statistical areas (MSA) in which the Big Cities Health Coalition (BCHC) member health departments are located . The BCHWe obtained microdata from the Census Bureau's 2015–2019 five-year American Community Survey (ACS) public use microdata sample file, via IPUMS USA , and lim2.2We created two categorizations of workers: “essential workers” and “high-risk (of exposure) workers”. First, to create the “essential worker” category we applied the industry guidelines issued by the Department of Homeland Security Cybersecurity and Infrastructure Security Agency (CISA) to identify, “essential critical infrastructure workers” . We iden2.3We computed the proportion of US born and foreign-born Hispanic and NHW workers in “high exposure risk”, “essential worker” occupations, and the proportion of “essential workers” in both “high exposure” and “low exposure” risk occupations, by MSA. All analyses included person weights to ensure calculations were representative of the noninstitutionalized population at the MSA and national levels. We created absolute disparity measures by calculating the difference in the proportion of workers in an essential or high-exposure risk occupation that are foreign-born Hispanic and US born Hispanic workers, compared to NHW workers, and estimated 95% confidence intervals of this difference. We perform Kruskal-Wallis tests to estimate whether differences in proportions by MSA are statistically significant. All analyses were conducted using R version 4.0.2.3We included 2,323,346 observations across 27 MSAs, representing a total of 50,028,026 individuals . Of the We found substantial heterogeneity in the size of disparities comparing the proportion of US and foreign-born Hispanic/Latino essential or high exposure risk workers to NHW workers, though disparities ranged more for essential workers than high exposure risk, and differences were only significant across MSAs for essential workers (p<0.001). For high exposure risk occupations , the patA median of 81.2% of workers were employed in essential industries, with 81.1% of US born Hispanics, 86.9% of foreign-born Hispanics, and 78.2% of NHWs employed in essential industries . Appendi4We found that, across large metropolitan areas of the US, a large proportion of workers were categorized as workers in essential occupations, and a smaller proportion were categorized as at high-risk of exposure to infectious diseases. We found disparities in the proportion of foreign-born Hispanic/Latino and US born Hispanic/Latino essential workers versus NHW essential workers, though disparities varied substantially by MSA, and were larger for foreign-born Hispanics, while the percentage of workers at high risk of exposure did not differ on average. This finding is consistent with a national level analysis that found similar rates of high-risk exposure occupations among Hispanic/Latino and NHW workers .Though the data is limited, research suggests that workplace exposure accounts for a substantial proportion of community spread of SARS-CoV-2 . For exaGenerally, metropolitan areas include large proportions of health care workers, occupations categorized as essential by DHS , likely Disparities in COVID-19 outcomes differ by geography and wave  but cumuOur analysis has some limitations. The analysis reflects data from the 2015–2019 ACS, the most recently available data. The analysis does not reflect any changes in employment that may have occurred after 2019, including any potential impacts of the pandemic on employment. Further research should examine which specific occupations or industries drive the observed disparities, and other potential explanations for metro-specific differences in disparities. Additionally, few analyses in the US consider occupational class, instead opting to analyze income or educational differences as measure of socioeconomic status, but occupational class analysis may produce differential estimates of impact and disparities, and so deserve further exploration . The lacOur work has implications beyond the immediate pandemic. The occupational and household risk we describe are also relevant for other infectious disease such as influenza. Previous analysis showed similar patterns of disproportionate occupational exposure during the 2009 H1N1 pandemic for Hispanics/Latinos versus NHWs . In prepAs racial capitalism highlights, solutions to occupational disparities need to address the intersecting exploitation of capitalism and racism in structuring occupational inequities . This su5This research highlights disparities in the proportion of US and foreign-born Hispanic/Latino essential workers, compared to NHW essential workers, in large MSAs across the US. We identify one disparity that may contribute to understanding observed racial and ethnic disparities in COVID-19, and potentially other respiratory diseases. Local area specific estimates of racial/ethnic disparities in occupational risk can help cities plan and target interventions to mitigate risk among specific occupational and racial/ethnic groups at elevated risk of exposure to infectious respiratory disease, and potentially help explain differences in disparities by metropolitan area.Alina Schnake-Mahl was holds equity, and currently consults for Cityblock Health.AS and UB conceived the study and drafted the first version of the manuscript. AS conducted the statistical analysis with support from KD, MA, and UB. NE supported the literature review. All authors reviewed the manuscript for critical intellectual content and have approved the final version.10.13039/100000002National Institutes of Health under award number DP5OD26429; and the 10.13039/100000867Robert Wood Johnson Foundation (10.13039/100000867RWJF) under award numbers 77644 and 78325. ML was supported by NIH/10.13039/100006545National Institute on Minority Health and Health Disparities R21MD012352-02S1. The funding sources had no role in the analysis, writing or decision to submit the manuscript.This study was supported by the Office of the Director of the The authors declare no conflict of interest.


The COVID-19 pandemic has spread uncertainty, promoted psychological distress, and fueled interpersonal conflict. The concomitant upsurge in endorsement of COVID-19 conspiracy theories is worrisome because they are associated with both non-adherence to public health guidelines and intention to commit violence. This study investigates associations between endorsement of COVID-19 conspiracy theories, support for violent radicalization (VR) and psychological distress among young adults in Canada. We hypothesized that (a) endorsement of COVID-19 conspiracy theories is positively associated with support for VR, and (b) psychological distress modifies the relationship between COVID-19 conspiracy theories and support for VR. A total of 6003 participants aged 18–35 years old residing in four major Canadian cities completed an online survey between 16 October 2020 and 17 November 2020, that included questions about endorsement of COVID-19 conspiracy theories, support for VR, psychological distress, and socio-economic status. Endorsement of conspiracy theories was associated with support for VR in multivariate regression  0.80–0.96). There is a significant interaction effect between endorsement of COVID-19 conspiracy theories and psychological distress . The magnitude of the association was stronger in individuals reporting high psychological distress  compared to those reporting low psychological distress . The association between endorsement of COVID-19 conspiracy theories and VR represents a public health challenge requiring immediate attention. The interaction with psychological distress suggests that policy efforts should combine communication and psychological strategies to mitigate the legitimation of violence. Countering violent radicalization (VR), defined as an “individual or collective process whereby normal practices of dialogue, compromise and tolerance between groups/individuals with diverging interests are abandoned and one or more groups/individuals engage in violent actions to reach a specific goal,”  is a pubThis past year, the COVID-19 pandemic has impacted and interacted with VR in troubling ways. The pandemic has accentuated structural violence, including systemic racism and socio-economic disparities , which eOne strategy used by extremists to sow dissent is to endorse conspiracy theories about the origins of the virus and authorities’ handling of the pandemic ,9. COVIDCOVID-19 conspiracist ideation is associated with greater anxiety and feelings of powerlessness , both inThroughout history, conspiracy theories have been a part of pandemics and epidemics. As far back as the medieval black plague, conspiracy theories proliferated to provide meaning and assign responsibility of the perceived threat to outgroup individuals, either marginal or strangers ,18. ThusThe association between psychological distress and support for VR has been repeatedly corroborated ,21; in cThis study aims to investigate associations between endorsement of COVID-19 conspiracy theories, psychological distress and sympathy for VR in a large sample of young adults living in four Canadian urban settings . We hypothesised that (a) support for VR is positively associated with endorsement of COVID-19 conspiracy theories, and (b) there is an interaction effect of psychological distress and endorsement of COVID-19 conspiracy theories on support for VR.In total, 6003 individuals aged 18–35 completed an on-line survey, of which 54.8% were women . Participants are all registered in the AskingCanadians pool, a Delvinia Technology Inc. online data collection firm with access to more than one million Canadian professionals and consumers who are nationally representative by region and monitored against Statistics Canada. The firm emailed potential participants an introductory message with a hyperlink to the survey. Participants received a gift card valued at 2.50$ according to how much time they dedicated to the survey. Ethics approval was obtained by X (BLINDED FOR REVIEW) before initiating the study, and all participants provided an electronic informed consent.Endorsement of COVID-19-related conspiracy theories was assessed with questions asking participants to rate, on a Likert scale from 1 = do not agree to 5 = agree completely, their level of agreement with four statements adapted from Freeman et al. : “The goThe Sympathies for Radicalization scale (SyfoR)  consistsThe Radicalism Intention Scale (RIS) is a subscale of the validated Activism and Radicalism Intention Scales (ARIS). A previous validation with ethnically diverse populations yielded adequate internal consistency and discriminant validity . The RISThe Hopkins Symptom Checklist-25 (HSCL-25) is a self-report questionnaire aimed at screening for levels of anxiety and depression. Items are rated on a Likert scale from 1  to 4 (extremely), and a total score is obtained by computing the mean of all items. The clinical cut-off is set at 1.75 (score range from 1 to 4). This means that an individual with a score of 1.75 or more can be considered as having high psychological distress. The HSCL-25′s psychometric qualities and transcultural validity have been well established among different cultural groups ,27. CronParticipants self-reported age, city of residence , gender , and immigrant generation . The financial problems variable was collected using the question “Presently in your household, are you experiencing difficulties related to lack of money?” , and educational level was collected with the question “What is the highest grade you completed?” .mice, using 5 imputed datasets [p-values for differences in mean scores between categories were calculated using ANOVA. Effect size is reported as η2. Multivariate regressions and moderation analysis were adjusted for self-reported gender, age, city of residence, reported level of financial problems, educational level and immigrant generation. First, the association between VR and endorsement of COVID-19 conspiracy theories was established using linear regression adjusted for the listed covariates. Second, moderation was identified using an interaction term for endorsement of COVID-19 conspiracy theories and the continuous mean score for psychological distress in the regression of sympathy for VR. Finally, the association between endorsement of COVID-19 conspiracy theories and sympathy for VR was estimated in strata below and above the clinical cut-off for HSCL-25.Missing data were imputed with multiple imputation chained equations, R-package datasets . For TabAt the descriptive level, mean total SyfoR and endorsement of COVID-19 conspiracy theories scores were higher for self-reported men compared with women, and lower in first- and second-generation immigrants compared with individuals from families residing in Canada for three or more generations. A majority of respondents (69.1%) reported no or little financial problems, but those who did also had higher levels of sympathy for VR, endorsement of COVID-19 conspiracy theories, and psychological distress. Regarding educational level, sympathy for VR, endorsement of COVID-19 conspiracy theories, and psychological distress were highest for individuals with a technical degree or some college/university. Scores on sympathy for VR, endorsement of COVID-19 conspiracy theories, and psychological distress were all higher in younger individuals (age 18–25 compared to 26–35). Among the four cities, participants in Montreal reported the highest unadjusted scores on the SyfoR, endorsement of conspiracy theories and psychological distress. Almost half of the total sample reported psychological distress mean scores above the clinical cut-off 1.75. In Montreal, this proportion was 56.1%.In multivariate regression, endorsement of conspiracy theories was significantly associated with SyfoR scores  0.80–0.96).  First geA significant interaction (moderation) was seen between endorsement of COVID-19 conspiracy theories and psychological distress continuous mean scores .  The magnSensitivity analyses using the RIS as outcome showed results in the same direction as for SyfoR .To the best of our knowledge, this is the first study to provide evidence of a worrisome phenomenon: the association between endorsement of COVID-19 conspiracy beliefs and support for VR during the present health emergency among a large sample of young adults in four different urban settings in Canada. Further, the study shows moderation of this association by psychological distress. Prior research suggests that endorsement of COVID-19 conspiracy theories is problematic from a public health perspective, because it may hinder following public health guidelines during the pandemic , 9, 10. Aligned with previous North American studies of VR, support for VR scores were lower among women, older participants, and first-generation immigrants. Of importance, the same socio-demographic factors emerged as protective in association with endorsement of COVID-19 conspiracy theories, further highlighting commonalities between the two phenomena. Thus, prevention and intervention programs to reduce both conspiracy beliefs and support for VR should support young adult men and gender minorities, and target majority groups rather than immigrant groups. In this study, the non-linear association between socio-economic status and support for VR is noteworthy. Despite the importance of social inequities as a driver of VR, the literature has traditionally reported a weak association between poverty and this outcome . During There are several limitations to this study. First, this is a cross-sectional study; thus we cannot make causal claims and, similarly to previous research, have not been able to ascertain the temporality of psychological distress and conspiracist ideation . NonetheGiven our findings, we argue that public health communication strategies regarding COVID-19, which thus far have focused predominantly on cognitive dimensions of disinformation (i.e., deconstructing conspiracy


Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains.This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. The primary outcome is all-cause mortality. The association of risk variables and all-cause mortality was assessed using Cox proportional hazards models. Machine and deep learning approaches were used to improve overall survival prediction and were evaluated with fivefold cross validation method.A total of 273 678 patients  months) were included, with 91 155 deaths occurring on follow-up . Multivariate Cox regression found the following significant predictors of all-cause mortality: age, male gender, baseline comorbidities, anemia, mean values of neutrophil-to-lymphocyte ratio, high-density lipoprotein-cholesterol, total cholesterol, triglyceride, HbA1c and fasting blood glucose (FBG), measures of variability of both HbA1c and FBG. The above parameters were incorporated into a score-based predictive risk model that had a c-statistic of 0.73 (95% CI 0.66 to 0.77), which was improved to 0.86 (0.81 to 0.90) and 0.87 (0.84 to 0.91) using random survival forests and deep survival learning models, respectively.A multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus. The predictive and modeling capabilities of machine/deep learning survival analysis achieved more accurate predictions. Increased variability in metabolic parameters is predictive of higher mortality in type 2 diabetes mellitus.We developed a machine learning-driven predictive risk model for type 2 diabetes mellitus using multiparametric approach with data from different domains.Measures of variability of fasting glucose and HbA1c show similar predictive power for all-cause mortality, regardless of whether adjustments were made for initial values or mean values across follow-up.A multiparametric predictive risk model incorporating variables from different domains, including baseline demographics, comorbidities and laboratory tests, measures of variability of HbA1c and fasting blood glucose predicted all-cause mortality accurately.Machine learning-driven algorithms further improved the accuracy of the predictive models.A simple, easy-to-use score-based system has been devised to enable rapid risk prediction in the clinical setting.Type 2 diabetes mellitus is one of the most common metabolic conditions, with an increasing prevalence attributable to aging, sedentary lifestyles, environmental changes and better disease management.18In this territory-wide study, with the aid of machine/deep learning approaches, we developed a risk model for mortality prediction using multiparametric data from different domains. These include baseline comorbidities, measures of variability of fasting glucose and HbA1c, inflammatory and nutritional indices and drug prescription details. We tested the hypothesis that machine learning methods  codes for type 2 diabetes mellitus, and attended any of the 43 public hospitals or their associated ambulatory or outpatient facilities managed by the Hong Kong Hospital Authority between January 1 and December 31, 2009. The Clinical Data Analysis and Reporting System, a healthcare database that integrates patient information to establish comprehensive medical records with accurately linked mortality data were used in this study. This system has been used for epidemiological research by multiple research teams, including our team, in the past,25 26Baseline patient characteristics include demographic details such as age and sex, prior comorbidities (heart failure (HF), ischemic heart disease (IHD), ischemic stroke, aborted sudden cardiac death (SCD) of all causes including acute myocardial infarction, atrial fibrillation (AF), peripheral vascular disease, intracranial hemorrhage, osteoporosis, dementia, hypertension, chronic obstructive pulmonary disease (COPD), cancer, renal and ophthalmological diabetic complications), antidiabetic and cardiovascular medications. The ICD-9 codes for the aforementioned comorbidities are summarized in 10.1136/bmjdrc-2020-001950.supp1Supplementary dataThe following laboratory data were collected at baseline: neutrophil-lymphocyte ratio (NLR) was derived by dividing the absolute neutrophil by the lymphocyte count, anemia defined as <13 g/dL for men and <12 g/dL for women, biochemical test results including (1) creatinine, sodium, potassium, (2) urea, (3) albumin and total protein, (4) alanine aminotransferase and alkaline phosphatase, (5) FBG and HbA1c; (6) high-density lipoprotein-cholesterol (HDL-C), directly measured low-density lipoprotein-cholesterol (LDL-C), total cholesterol, and triglyceride.The number of antidiabetic drugs by class were extracted: (1) insulin, (2) biguanide, (3) sulphonylurea, (4) alpha-glucosidase inhibitor, (5) thiazolidinedione, (6) dipeptidyl peptidase-4 inhibitor, (7) glucagon-like peptide receptor-1 agonist, (8) meglitinide. Similarly, the number of antihypertensive medications of the following classes were also extracted: (1) angiotensinogen-converting-enzyme inhibitor/angiotensin receptor blocker, (2) beta-adrenergic receptor blocker, (3) calcium channel blocker, (4) diuretics. Lipid-lowering agents were also extracted.To calculate FBG and HbA1c variability, data points were obtained for the period between January 1, 2004 and December 31, 2008. Only patients with three or more measurements for the specific parameter were included for the variability analysis of the respective parameter. The different measures are detailed below and summarized in The primary outcome for the present student is all-cause mortality. Univariate Cox regression was applied to identify significant predictors for all-cause mortality and HR with 95% CI were reported. Variables achieving p<0.10 were included in a diabetes duration-adjusted multivariate model. Statistical significance is defined as p<0.05. FBG and HbA1c variability of the same formula were paired and added to the multivariate model to assess their predictiveness through comparison of HR, thus preventing problems with collinearity.To generate a predictive score, Cox regression was repeated for the final multivariate model with measures of variability included. HR between 1 and 1.50 was awarded 1 mark in the score. To adjust for the U-shaped relationship against mortality reported for HDL-C, LDL-C, total cholesterol and HbA1c, these parameters were first divided by deciles to serve as cut-offs and undergo univariate Cox regression. Thereafter, the decile with the smallest HR was selected as the reference and compared against the remaining deciles through univariate Cox regression again. The minimum and maximum cut-offs for the deciles that had an insignificant difference with the reference decile were selected as the cut-offs to be used in the score. To demonstrate the U-shaped relationship, the HR of deciles was plotted graphically. Similar methods were employed to illustrate the U-shaped relationship by existing studies.To further evaluate the predictive value of the measures of variability, the measures were also divided into quartiles, with the first quartile as a reference, to perform univariate Cox regression and assess the AUC of the quartile cut-offs. The quartile HR of the FBG and HbA1c measures of variability were illustrated graphically. Statistical analyses were performed using RStudio software (V.1.1.456) and Python (V.3.6).et al.30Machine/deep learning survival analysis models can directly capture the relationships between risk predictors and mortality outcome without prior functional assumptions typically made in Cox analysis models. Here we used an RSF model, a type of machine learning method for survival analysis, relying on the intuition that the best survival learning model, when combined with weak decision tree learning models, can minimize the overall survival prediction errors. The prediction errors are measured by performance evaluators, for example, precision, recall, AUC and C-index. The out-of-bag (OOB) method was adopted whenever a bootstrap sample (bag ones) is down with replacement from the training dataset. The bootstrapping technique is used to grow the tree and results in well-defined subsets. Some of the bootstrap are duplicates and are members of the in-bag subset, and the remaining individuals define the OOB subset for the final tree. Each individual in the OOB subset for a tree is passive. A unique terminal node membership and terminal node statistic were assigned. An OOB ensemble statistic for each individual is formed by combining the terminal node statistics from all trees where an individual is an OOB member. Finally, the class with the maximum frequency in the OOB ensemble statistic serves as the predicted class label for the member. More detailed descriptions of these concepts were described by Breiman The variable’s importance of interest is calculated as the prediction error (squared loss) of the original ensemble event-specific cumulative probability function subtracted from the prediction error of the original ensemble event-specific cumulative probability function (obtained when each OOB instance is just dropped down its in-bag competing risks tree).We further employed a nonlinear deep learning survival method termed Cox proportional hazards DeepSurv approach. This can inherently and adaptively model the high-level interaction patterns among risk predictors and thus can better capture the complex nonlinear relationship between patients’ covariates  and mortality outcome directly. Specifically, DeepSurv is a deep feed-forward neural network that can predict the effects of a patient’s baseline covariates on their hazard rate parameterized by the weights of the neural network. The input of DeepSurv is the baseline variables of the patient with diabetes. The hidden layers of DeepSurv consist of a fully connected layer of nodes, followed by a dropout layer.35randomForestSRC (V.2.9.3), ggplot2 (V.3.3.2), and python package DeepSurv (V.0.1.0) were used to generate the mortality prediction results.The RSF, DeepSurv and multivariate Cox regression models adopted the same set of predictors. A fivefold cross-validation approach was performed to compare the survival prediction performance of RSF and DeepSurv in terms of precision, recall, AUC and HC-index over the standard Cox model. The R packages, The study cohort included 273 876 patients  with a median follow-up of 142 (IQR (IQR)=106–142) months, which corresponded to a total of 2 660 465 patient-years. The baseline demographics, clinical, laboratory and drug details are shown in Over a median follow-up period of 142 (IQR=106–142) months, 91 155 deaths were recorded (33.3%), which corresponded to an annualized mortality rate of 3.43%. The significant univariate predictors for all-cause mortality are presented in The following parameters remained significant predictors following multivariate adjustment : (1) ageA score-based predictive risk model for all-cause mortality was developed by incorporating significant predictors from multivariate analysis. One point was allocated for each significant predictor where the HR was less than 1.5, and 2 points for HRs between 1.5 and 2.5. Out of the eight measures of variability for HbA1c and FBG, SD had the highest HR and greatest statistical significance when adjusted to the multivariate model . It was therefore selected to be included in the mortality score. Altogether, the predictive risk model had a total score out of 25 . ROC anaA RSF model was further performed to predict mortality outcome. The optimal tree number of the RSF model selected as 400 using a fivefold cross-validation approach to minimize the overall squared error rate in the testing set is shown in Finally, we compared the survival analysis performance of the RSF model and DeepSurv as typical machine learning and deep learning approaches, respectively, over multivariate Cox model to predict the mortality outcome of the patients with diabetes using the fivefold cross-validation method. Sobol solver38The comparative performance results of the different models are shown in In this study, we developed a machine learning-driven predictive risk model for type 2 diabetes mellitus using a multiparametric approach with data from different domains. Our novel findings are that (1) measures of variability of fasting glucose and HbA1c show similar predictive power for all-cause mortality, regardless of whether adjustments were made for initial values or mean values across follow-up; (2) a multiparametric predictive risk model incorporating variables from different domains, including baseline demographics, comorbidities and laboratory tests, measures of variability of HbA1c and FBG predicted all-cause mortality accurately and (3) machine learning-driven algorithms further improved the accuracy of the predictive models.Numerous factors have been associated with premature mortality in patients with type 2 diabetes mellitus. Prior epidemiological studies have identified key risk factors including age, comorbidities, healthcare utilization patterns and laboratory findings.Diabetes mellitus is characterized by the presence of systemic chronic inflammation, which is accompanied by increased oxidative stress. To quantify the degree of inflammation, the NLR has been used as a surrogate measure, as it reflects the balance between proinflammatory and anti-inflammatory pathway activation. In our cohort, we found that raised NLR was associated with all-cause mortality risk. We extend previous findings of our group and other groups that increased NLR has been associated with insulin resistance in patients with newly diagnosed type 2 diabetes,47 48Glycemic variability refers to the fluctuations in glucose levels and can be measured as a daily variation or variation between different clinical visits.Standard survival model such as Cox proportional hazards model is a semiparametric analysis model to calculate the effects of observed patient’s covariates on the mortality risk outcome. The Cox model assumes the effect of each covariate is proportional. However, in many practical applications, the assumption is not true and risks losing decision information among the observed patient’s covariates. Furthermore, it cannot account for the presence of U-shaped relationships as only a single HR is derived for each covariate. Therefore, numerous nonlinear survival models were developed to better fit survival data with nonlinear log-risk functions (eg, time-encoded methodsThe findings of this study illustrate that machine/deep survival learning models can better capture the highly complex and nonlinear relationships between prognostic variables and an individual patient’s risk of mortality without prior variable selection or domain knowledge, compared with the traditional Cox analysis model. Application of machine/deep learning to survival analysis performs much better than the standard Cox model in predicting mortality risk of patients with diabetes mellitus. Additionally, machine/deep survival learning models will enable clinicians to provide personalized survival estimations based on the computed probability of mortality risk. In practice, medical researchers can use machine/deep survival learning models to improve overall survival prediction performance based on prognostic characteristics of the patients with diabetes mellitus and subsequently inform early efficient treatment options and even reduce mortality risk.The following strengths of our study should be noted. First, this was a territory-wide study with large patient numbers with complete and long follow-up of mortality over 10 years, owing to the linkage of the electronic health records to the death registry. Second, the availability of different data types including prior comorbidities, laboratory test results that included longitudinal data and drug details meant that we were able to build a comprehensive risk model for accurate prediction. Third, the application of the latest machine learning techniques was able to further improve the risk predictions of the models.However, there are some limitations that should be noted. First, this was a retrospective study and therefore carries the potential bias, such as information bias, that is found in all studies of this type. Second, as with all studies using administrative databases, undercoding is a possibility. This was nevertheless mitigated by our definition of diabetes to include patients with the appropriate ICD coding and those who were on any diabetic medication or met the criteria of diabetes by either HbA1c or fasting glucose results. Patients with type 1 diabetes mellitus were not included given a different disease course and pathogenesis. Further research is needed to explore the potential for the present findings to be extrapolated onto patients with type 1 diabetes mellitus. Third, although the deep neural network survival learning approach demonstrates significant potential in providing much more accurate predictions, the model’s weak interpretability becomes the main obstacle for its real application in clinical practices. Investigations of developing interpretable deep survival learning models that provide highly accurate predictions with supportive explanations for patients with diabetes mellitus become our next research concentration.A multiparametric model incorporating variables from different domains predicted all-cause mortality accurately in type 2 diabetes mellitus and a machine/deep learning-driven approach provided further improvements for risk prediction.