Risk of developing type 2 diabetes according to FINDRISC and socioeconomic status

Diabetes mellitus (DM) is a major global health issue, with type 2 diabetes (T2D) accounting for over 90% of cases. Community pharmacies, given their accessibility, are well positioned to assist in early detection and management of T2D. This study evaluated post-pandemic T2D risk in a Portuguese population using the Finnish Diabetes Risk Score (FINDRISC) across five community pharmacies. A total of 494 participants aged 40 or older without a prior diagnosis of diabetes were assessed. The mean FINDRISC score was 12.3, and 29.8% were identified as high or very high-risk, with 8.7% referred to general practitioners for follow-up based on elevated glycated hemoglobin (HbA1c). Key risk factors include age, body mass index, waist circumference, lack of physical activity, and family history of diabetes. Lower educational levels were also associated with higher diabetes risk. Community pharmacies are shown to play an essential role in screening and educating at-risk populations, emphasizing the importance of physical activity, healthy diets, and regular monitoring. These findings reinforce the value of community pharmacists in mitigating T2D risk and enhancing public health outcomes through cost-effective, validated screening tools like FINDRISC. Finally, pre-pandemic FINDRISC studies discussed show similar results suggesting that the COVID-19 pandemic did not significantly impact the overall risk profile for T2D.

Type 2 diabetes (T2D) represents a major public health challenge in Poland. This study investigated geographic heterogeneity and municipality‑level ecological predictors of a high T2D risk in the Świętokrzyskie Voivodeship (Poland), a region undergoing rapid socioeconomic transition. We aimed to identify associations between the T2D risk, assessed by the Finnish Diabetes Risk Score (FINDRISC), and socioeconomic and environmental factors. This cross‑sectional study analyzed data from 252 427 residents of the Świętokrzyskie Voivodeship aged 45-64 years, without diagnosed diabetes, who participated in a regional prevention program (2019-2022). Individual risk, assessed via the FINDRISC questionnaire, was linked with municipality‑level ecological data. We used a logistic regression model with municipality‑clustered standard errors to identify predictors of a high T2D risk (FINDRISC ≥15). Overall, 13.6% of the participants were at a high risk of diabetes (FINDRISC ≥15), with significant geographic variation (P <0.001). Among municipality‑level predictors, higher unemployment rate was significantly associated with increased odds of a high T2D risk (odds ratio [OR], 1.14 per 1% increase; P <0.001), whereas higher proportions of legally disabled residents and higher annual mean concentrations of particulate matter with aerodynamic diameter of 2.5 μm or smaller were inversely associated with the prevalence of a high T2D risk (OR, 0.98; P = 0.03 and OR, 0.92 per 1 μg/m3; P = 0.001, respectively). Results were robust across sensitivity analyses using alternative FINDRISC cutoffs. Unemployment was a key population‑level determinant of a high T2D risk, whereas other socioeconomic and environmental factors showed null or inverse associations. These findings underscore the importance of considering local context when assessing population‑level health determinants.

Background: Diabetes mellitus is a real public health problem worldwide and is growing in developing countries. Our aim was to determine the prevalence of undiagnosed type 2 diabetes mellitus (T2DM) and to evaluate the performance of the Finnish Diabetes Risk Score (FINDRISC) questionnaire to identify type 2 diabetics in the urban population of Ouagadougou, Burkina Faso. Methodology: This was a cross-sectional study among volunteers aged 18 years and older recruited systematically from November 11 to 16, 2019, in the city of Ouagadougou, Burkina Faso, FINDRISC score was used. Analysis of the Receiver Operating Characteristic (ROC) curve was used to study the diagnostic performance of FINDRISC for the identification of type 2 diabetics. The optimal threshold was determined by the sum of the highest sensitivity and specificity. Multivariate logistic regression was used to analyze the association of each variable used in the calculation of the FINDRISC score. Results: A total of 1276 individuals were included in the analyses, of which 667 (52.27%) were women. The average age was 34.16 years (SD: ±12.42). The prevalence of T2DM was 10.74%. The mean FINDRISC score was 5.85 (SD: ±4.31). The majority (58.54%) of individuals had a low risk of diabetes according to the FINDRISC score 0 - 7, while 3.61% had a score ≥ 15. The FINDRISC score showed good performance (AUC = 0.70) in identifying undiagnosed type 2 diabetics. However, the variables in the score that best predicted the likelihood of being diabetic were age (p < 0.001), daily physical activity (p = 0.004), use of antihypertensive medication (p = 0.007) and waist circumference (p < 0.001). The optimal cut-off score ≥ 7 was the best predictor of the likelihood of having T2DM. Conclusion: The Finnish Risk Score (FINDRISC) is a good predictor of the risk of dysglycemia in Burkina Faso. It is a score to be promoted in daily clinical practice because it is easy to use, affordable and non-invasive. Further studies are needed to make modifications to the FINDRISC questionnaire in case it is applied to other ethnic groups.

Evaluation of the Finnish Diabetes Risk Score (FINDRISC) for diabetes screening in Kayseri, Turkey

The aim of this study was to assess the performance of the Finnish Diabetes Risk Score as a screening tool for undetected type 2 diabetes (T2D), abnormal glucose tolerance (AGT) and metabolic syndrome in the general population. In a cross-sectional, population-based survey, a total of 4,622 subjects aged 45-74 years were invited to a health examination that included an oral glucose tolerance test. Full data with risk score estimate and glucose tolerance status were available for 2,966 subjects without a prior history of diabetes. The risk score was associated with the presence of previously undiagnosed T2D, AGT, metabolic syndrome and cardiovascular risk factors. The area under the receiver operating curve for the prevalence of undiagnosed diabetes was 0.72 in men and 0.73 in women. The sensitivity using a cutoff risk score of 11 to identify undiagnosed diabetes was 66% in men and 70% in women; the corresponding false-positive rates were 31% and 39%, respectively. The area under the receiver operating curve for detecting the metabolic syndrome was 0.72 in men and 0.75 in women. The Finnish Diabetes Risk Score can be used as a self-administered test to screen subjects at high risk for T2D. It can also be used in the general population and clinical practice to identify undetected T2D, AGT and the metabolic syndrome.

To evaluate a modified Finnish Diabetes Risk Score (FINDRISC) for predicting the risk of incident diabetes among white and black middle-aged participants from the Atherosclerosis Risk in Communities (ARIC) study. We assessed 9754 ARIC cohort participants who were free of diabetes at baseline. Logistic regression and receiver operator characteristic (ROC) curves were used to evaluate a modified FINDRISC for predicting incident diabetes after 9 years of follow-up, overall and by race/gender group. The modified FINDRISC used comprised age, body mass index, waist circumference, blood pressure medication and family history. The mean FINDRISC (range, 2 [lowest risk] to 17 [highest risk]) for black women was higher (9.9 ± 3.6) than that for black men (7.6 ± 3.9), white women (8.0 ± 3.6) and white men (7.6 ± 3.5). The incidence of diabetes increased generally across deciles of FINDRISC for all 4 race/gender groups. ROC curve statistics for the FINDRISC showed the highest area under the curve for white women (0.77) and the lowest for black men (0.70). We used a modified FINDRISC to predict the 9-year risk of incident diabetes in a biracial US population. The modified risk score can be useful for early screening of incident diabetes in biracial populations, which may be helpful for early interventions to delay or prevent diabetes.

Background: Shared medical appointments (SMA) via home telemedicine may improve clinic attendance and adherence to care recommendations in adolescent and young adult patients (AYA) with type 1 diabetes (T1D). Participation in home telemedicine requires basic health literacy, reliable access to high-speed Internet on a compatible device, and a private location for attending appointments. AYA from households with lower socioeconomic status (SES) may encounter barriers to participation in home telemedicine due to limited resources. Objective: Evaluate the feasibility of conducting SMA via home telemedicine for low SES AYA with T1D. Methods: We conducted baseline patient and family assessments as part of a prospective study on the use of SMA and telemedicine for AYA with T1D who attend a pediatric outpatient endocrinology clinic. We calculated SES for each family using a modified version of the Hollingshead index, and dichotomized patients into low and high SES groups. Results: AYA reported nearly equal interest in attending SMA (Low: 76%; High: 66%), and in completing appointments online (Low: 41%; High: 45%), regardless of SES. Patients reported having access to high-speed Internet (100%), favored home appointments (Low: 35%; High: 42%), and reported having private space (Low: 83%; High: 88%). Low SES patients were younger than high SES patients (15 vs. 17 years, p = 0.01), and reported shorter disease duration (6 vs. 9 years, p &amp;lt; 0.01). Low SES patients reported needing help reading medical information at least sometimes more frequently (76%) than high SES patients (56%, p = 0.05). However, this effect was attenuated in multiple regression analysis, where variations in patients’ health literacy were associated with age (p &amp;lt; 0.05) instead of SES. Conclusions: Low SES AYA with T1D are equally equipped and interested in utilizing shared telemedicine as high SES patients. Home telemedicine may be a feasible format for diabetes care and psychosocial support for all patients, regardless of SES. Disclosure J.J. Flores Garcia: None. M.W. Reid: None. J. Raymond: None.

&lt;p dir="ltr"&gt;&lt;b&gt;Background&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;A credible public health survey or surveillance program is judged by its ability to measure intended outcomes accurately and cost effectively. However, in the pursuit of operational efficiency, such programs risk introducing bias in their estimates. This thesis examines several key potential sources of bias in public health surveys, focusing on three main domains: the characteristics and selection of respondents paying attention to the hard-to-reach late respondents, the use of mobile phone technology for data collection, and the adaptation of standardized measurement tools-specifically the Framingham Risk Score (FRS) and the Finnish Diabetes Risk Score (FINDRISC). The tools are internationally recognized for estimating the 10-year risk of cardiovascular disease and type 2 diabetes, respectively. By exploring these domains, this work aims to highlight critical methodological considerations that survey designers and implementers must consider minimizing measurement bias and enhance data validity.&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;Methods&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;The study was conducted within the Rakai Community Cohort Study (RCCS), a long-standing surveillance program in south-central Uganda. Covering 34 diverse communities, the RCCS focuses on HIV and other health priorities. In each round, 70-80% respond on time, while late respondents require extra effort from the researchers to track them. Study I examined whether late respondents differ from early ones and if their (late respondents) exclusion could bias results. We conducted descriptive analyses and compared these groups using Chi-square tests. Multivariable logistic regression was used to adjust for confounders, reporting adjusted odds ratios (AORs) with 95% confidence intervals. We also modelled interactions with age to estimate marginal predictive means (MPMs), illustrating how the likelihood of late response varies across age groups. The results are reported in constituent manuscript I. The use of mobile phones for population-based surveys is an ongoing global discussion, particularly in resource-limited settings. We leveraged RCCS Rounds 19 and 18 data, collected around the COVID-19 period, and data from a concurrent mobile phone-based surveillance in the same population to compare participation rates by survey modality (face-to-face vs. mobile phone surveys), we assessed phone access, and characterized the differences between respondents reached and missed by each method. The primary independent variable was interviewing modality, with adjustments made for sex, age, community type, HIV status, and other covariates. Robust standard errors accounted for clustering at the individual level. We also examined longitudinal trends in mobile phone ownership, including the frequency of mobile phone number change, the time to change of numbers and multiple SIM ownership. Phone number change was defined as the complete replacement of previously recorded numbers between survey rounds, excluding partial changes. Rates and associated factors were estimated using Poisson regression with generalized estimating equations (GEE), while time to number change was assessed using the Andersen-Gill Cox model to account for repeated measurements. The results are reported in studies II (face-to-face vs mobile phone surveys) and study III (mobile phone ownership, numbers change and time to change analyses) We conducted qualitative exit interviews to assess participants' experiences with the FRS and FINDRISC risk score tools. Interviews were held on the same day, immediately after participants completed the questionnaires and measurement procedures. The analysis, based on 15 interviews, followed an iterative approach. Thematic coding was used to identify and summarize key themes that we report in constituent study IV.&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;Results&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;Overall, 68,263 participants were included in the late respondent analysis. Men were 22% times more likely to be late respondents than women (23% vs. 19%, respectively). This was true for younger participants 15-19 years old relative to 40+years old participants. Compared to the unemployed, participants engaged in formal employment followed by those engaged in fishing were more likely to be late respondents (28% and 27% respectively). When comparing response times between people living with HIV and those who are HIV-negative, no significant difference was observed (AOR=1.06; 95% C.I .: 0.99, 1.13). In women, HIV status had no effect on the marginal predictive mean (MPM) of being late, which declined with age in both groups. Among young men, MPM of being a late respondent was significantly higher in those with HIV but decreased with age. Conversely, in HIV- negative men, the MPM increased with age. In study II, we observed 90% access to mobile phones, with lower access among older people, and people living with HIV. When including only individuals who participated in the previous RCCS survey round, participation in the face-to-face survey (82%) was higher than participation in the mobile phone survey (75%, p &lt; . 001). Survey participation was higher among people living with HIV compared to HIV-negative individuals (84% vs 82%, p&lt; . 001) in the face-to-face survey. In study III we assessed mobile phone ownership. A total of 97,034 participants were included in this analysis. Overall, 61.8% reported owning a phone. Mobile phone ownership increased by 33% over the study period, from 51% in 2010 to 68% in 2020 (p&lt;0.001). Ownership was higher among men. There was no difference in phone ownership by HIV status (adjPR=1.01, 95% CI 0.97-1.05). About 75% of participants who reported more than one sexual partner in the past 12 months owned a mobile phone, compared to 58% who reported zero or one partner in the same period (p&lt;0.001). Phone number change is as high as 15-19/100 person years and consistent across the ten years of observation.&lt;/p&gt;&lt;p dir="ltr"&gt;When we examined participants' experiences with FRS and FINDRISC, we found that overall, the tools were clear and acceptable in this setting. Participants were comfortable with having their weights, waists, heights and other measurements taken if it was by a health worker. There were a few challenges with interpretation and measurement of physical activity, and dietary practice questions given the seasonal variations in their availability in the community.&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;b&gt;Conclusion&lt;/b&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;The studies reveal that late respondents are different and cannot be ignored therefore means to speed up their participation should be devised. The use of mobile phones is feasible, there are some differentials in those who are missed by phone surveys (especially men). Meanwhile, mobile phone ownership is on a rapid rise across both sexes with men slightly higher and women rapidly catching up (by 2020). However, the rate of phone number change is quite high and this needs to be considered. The FRS and the FINDRISC scores are generally acceptable, however, some adaptation to match local practices and the seasonal dietary practices need to be addressed during survey planning, data analysis and interpretation.&lt;/p&gt;&lt;p dir="ltr"&gt;Key terms: Late respondents, Mobile phones, Bias, Framingham, Finnish Diabetes Risk Score.&lt;/p&gt;&lt;h3&gt;List of scientific papers&lt;/h3&gt;&lt;p dir="ltr"&gt;Paper I: Characterizing late respondents in the Rakai Community Cohort Study, 2012-2020, Uganda&lt;b&gt;. &lt;/b&gt;&lt;b&gt;Robert Ssekubugu&lt;/b&gt;, Zangin Zeebari, Hadija Nakawooya, Ping Teresa Yeh, Anthony Ndyanabo, Fredrick Edward Makumbi, Anna Mia Ekström, Grace Nalwoga Kigozi, Eli. M Binder, Kate Grabowski, David Serwadda, Victor Ssempijja, Larry W Chang, Godfrey Kigozi, Helena Nordenstedt [Manuscript]&lt;/p&gt;&lt;p dir="ltr"&gt;Paper II: Use of Mobile Phone to collect data on COVID-19; phone access and participation rates in Rakai, Uganda. &lt;b&gt;Robert Ssekubugu&lt;/b&gt;, Anthony Ndyanabo, Fredrick Edward Makumbi, Anna Mia Ekström, Laura Bere, Grace Nalwoga Kigozi, Hadijja Nakawooya, Joseph Ssekasanvu, Maria J. Wawer, Fred Nalugoda, Nelson Sewankambo, Victor Ssempijja, Betty Nantume, David Serwadda, Godfrey Kigozi, Ronald H. Gray, Larry W Chang, M. Kate Grabowski, Helena Nordenstedt &amp; Joseph Kagaayi Glob Health Action. 2024 Dec 31;17(1):2419160. &lt;a href="https://doi.org/10.1080/16549716.2024.2419160" rel="noreferrer" target="_blank"&gt;https://doi.org/10.1080/16549716.2024.2419160&lt;/a&gt;&lt;/p&gt;&lt;p dir="ltr"&gt;Paper III: Mobile phone ownership, number change, time to change and the implications to public health services delivery in Uganda, 2010-2020&lt;b&gt;. &lt;/b&gt;&lt;b&gt;Robert Ssekubugu&lt;/b&gt;, Ping Teresa Yeh, Hadija Nakawooya, Victor Ssempijja, Godfrey Kigozi, Joseph Kagaayi, Fred Nalugoda, Anna Mia Ekström, Betty Nantume, David Serwadda, Philip Kreniske, Zangin Zeebari, Michelle A. Moffa, Larry W. Chang, Kate M. Grabowski, Fredrick Makumbi and Helena Nordenstedt [Manuscript]&lt;/p&gt;&lt;p dir="ltr"&gt;Paper IV: Cardiovascular (Framingham) and type II diabetes (Finnish Diabetes) risk scores: a qualitative study of local knowledge of diet, physical activity and body measurements in rural Rakai, Uganda&lt;b&gt;. &lt;/b&gt;&lt;b&gt;Robert Ssekubugu&lt;/b&gt;, Fredrick Makumbi1, Rocio Enriquez, Susanne Rautiainen Lagerstrom, Ping Teresa Yeh, Caitlin E. Kennedy, Ronald H. Gray, Lilian Negesa, David M. Serwadda, Godfrey Kigozi, Anna Mia Ekström and Helena Nordenstedt BMC Public Health. 2022 Nov 29;22(1):2214. &lt;a href="https://doi.org/10.1186/s12889-022-14620-9" rel="noreferrer" target="_blank"&gt;https://doi.org/10.1186/s12889-022-14620-9&lt;/a&gt;&lt;/p&gt;

Until now, no systematic screening for T2D or prevention activities targeting T2D has been implemented in Colombia. The aims of this study were i) describe the feasibility of implementing the Finnish Diabetes Risk Score (FINDRISC) as a screening tool for glucose metabolism disorders (GMD) in the primary health care system in Barranquilla in Colombia during 2011 and 2012, and ii) to describe the risk factors for T2D in the population screened. This screening was opportunistic among people aged 34-60 years living in five primary health care catchment areas in Barranquilla, Colombia. People with 13 or more FINDRISC points were invited to an oral glucose tolerance test (OGTT). Out of 14193 participants with the FINDRISC completed, 35% (n=4915) had a score of 13 points or higher (men 23%, women 40%). Among those with FINDRISC completed, the percentage of people with BMI<25 kg/m2 was 46% in men and 35% in women. The prevalence of screen-detected T2D was 18% in men and 12% in women, respectively, among those with FINDRISC >12 attending an OGTT. In both sexes the prevalence of isolated IGT, isolated IFG, and IFG and IGT combined were 8%, 11%, and 8%, respectively. In total, 2% of all 14 193 screened participants had undetected T2D and 7% GMD. This figure would potentially be 4.6% (T2D), respectively 15% (GMD) if all with a FINDRISC>12 attend the OGTT. Thus, we found the FINDRISC to be a useful tool to identify people with GMD. This article is protected by copyright. All rights reserved.

Introduction Shift work is associated with type 2 diabetes mellitus (T2DM) partially explained through decreased insulin sensitivity by disruption of the day/night rhythm. Lifestyle interventions can prevent the onset of T2DM, and avoid complications. This study aimed to (1) report the prevalence of pre-diabetes and T2DM in shift workers, (2) study the impact of lifestyle advice on the risk for T2DM. Methods A two-step method was used: (1) the risk for T2DM was assessed by the FINnish Diabetes RIsk SCore (FINDRISC), (2) HbA1c was determined by finger prick when FINDRISC was ≥12. Results were discussed during medical consultation, and lifestyle advice was given. After three months, the evolution of the FINDRISC score and the HbA1c was evaluated. This study was approved by the ethics committee of Ghent University. Results The response rate was 47%; 44.6% of them were shift workers. 120 participants scored ≥12 on the FINDRISC. According to the HbA1c values, 26.7% had pre-diabetes and 3.3% had T2DM. There was a positive/weak correlation between FINDRISC score and HbA1c (r=0,29; p=0.003). No statistical links were found between shiftwork and FINDRISC (x²; p=0.502). After the intervention 14 of 23 persons had a lower FINDRISC (median from 14 to 12, p=0.010), no significant difference was found for Hba1c. Discussion No clear link was found between shift work and diabetes risk. Lifestyle advice did not affect HbA1c significantly after three months. Further research is needed to investigate the risk and preventive intervention among larger groups of shift workers. Conclusion (Pre-)diabetes can easily be detected via the two-step method.

Context:India is currently becoming capital for diabetes mellitus. This significantly increasing incidence of diabetes putting an additional burden on health care in India. Unfortunately, half of diabetic individuals are unknown about their diabetic status. Hence, there is an emergent need of effective screening instrument to identify “diabetes risk” individuals.Aims:The aim is to evaluate and compare the diagnostic accuracy and clinical utility of Indian Diabetes Risk Score (IDRS) and Finnish Diabetes Risk Score (FINDRISC).Settings and Design:This is retrospective, record-based study of diabetes detection camp organized by a teaching hospital. Out of 780 people attended this camp voluntarily only 763 fulfilled inclusion criteria of the study.Subjects and Methods:In this camp, pro forma included the World Health Organization STEP guidelines for surveillance of noncommunicable diseases. Included primary sociodemographic characters, physical measurements, and clinical examination. After that followed the random blood glucose estimation of each individual.Statistical Analysis Used:Diagnostic accuracy of IDRS and FINDRISC compared by using receiver operative characteristic curve (ROC). Sensitivity, specificity, likelihood ratio, positive predictive and negative predictive values were compared. Clinical utility index (CUI) of each score also compared. SPSS version 22, Stata 13, R3.2.9 used.Results:Out of 763 individuals, 38 were new diabetics. By IDRS 347 and by FINDRISC 96 people were included in high-risk category for diabetes. Odds ratio for high-risk people in FINDRISC for getting affected by diabetes was 10.70. Similarly, it was 4.79 for IDRS. Area under curves of ROCs of both scores were indifferent (P = 0.98). Sensitivity and specificity of IDRS was 78.95% and 56.14%; whereas for FINDRISC it was 55.26% and 89.66%, respectively. CUI was excellent (0.86) for FINDRISC while IDRS it was “satisfactory” (0.54). Bland-Altman plot and Cohen's Kappa suggested fair agreement between these score in measuring diabetes risk.Conclusions:Diagnostic accuracy and clinical utility of FINDRISC is fairly good than IDRS.

Inverse associations of educational level and household income (as proxy indicators of socioeconomic status) with cardiovascular disease risk factors are fairly well established. Whether differences in cardiovascular disease risk factors across education or income levels have widened in the last decade remains an issue of considerable public health importance. Analysis by mixed-regression models of trends in cardiovascular disease risk factors, in population-based samples (n = 3334 in 1980-1982, n = 4538 in 1985-1987, and n = 4517 in 1990-1992) of Minneapolis-St Paul residents 25 to 74 years old. Education level was inversely related to serum cholesterol level, systolic blood pressure, smoking prevalence, and body mass index and positively related to leisure-time physical activity and health knowledge in both sexes. Household income was inversely associated with systolic blood pressure and body mass index in women and with smoking prevalence in both sexes. Income level was positively associated with leisure-time physical activity and health knowledge in both sexes. There were overall favorable downward secular trends in serum cholesterol level and systolic blood pressure, favorable upward trends in health knowledge, and unfavorable upward trends in body mass index across all socioeconomic status groups. Throughout the decade, trends in smoking prevalence differed by education level in men (P = .01), such that declines were observed only in those with a college degree or some college education. With respect to trends in leisure-time physical activity, there were greater gains among men with low socioeconomic status (P = .03 for education; P = .02 for income) and among less affluent women (P = .001). These data support the inverse association between socioeconomic status and cardiovascular disease risk factors but suggest no widening (with the exception of smoking by education level in men) of socioeconomic differences in risk factor trends during the last decade in a representative sample of the Minneapolis-St Paul population.

BackgroundEvidence of modifiable risk factors for cognitive decline and dementia is accumulating, showing the potential of dementia risk reduction via lifestyle modification and cardiovascular risk management. People with low socioeconomic status (SES) have increased dementia risk and on average worse health. This study investigated whether the association between a modifiable dementia risk score and rate of cognitive decline differs across SES strata.MethodData were used from Maastricht Aging Study (MAAS), a prospective cohort study with a 12‐year follow‐up. Participants aged ≥40 years with complete dementia risk profiles were included (n = 1223). The validated ’LIfestyle for BRAin health’ (LIBRA) index was used to assess the modifiable dementia risk fraction. Cognitive performance was serially assessed at baseline, 6 and 12 years and measured in the domains of information processing speed, executive functioning and verbal memory function. A SES compound score was calculated from equivalent income and educational level and divided into tertiles (low, middle, high). Linear mixed models were used to study the association between LIBRA, SES and their interaction on the rate of cognitive decline.ResultParticipants in the lowest SES tertile displayed more decline in information processing speed (vs. middle SES: X2 = 7.08, p = 0.029; vs. high SES: X2 = 9.49, p = 0.009) and verbal memory (vs. middle SES: X2 = 9.28, p&lt;0.001; vs. high SES: X2 = 16.68, p&lt;0.001) compared to their middle‐ and high‐SES counterparts. Higher (unhealthier) LIBRA scores were also associated with more decline in information processing speed (X2 = 12.66, p = 0.002) and verbal memory (X2 = 4.63, p = 0.032). No consistent effect modification by SES on the association between LIBRA and cognition was found.ConclusionThis study shows that lower SES and higher modifiable dementia risk predict faster decline in information processing speed and verbal memory function over 12 years. Results suggest that lifestyle is an important determinant of cognitive decline across SES groups. Yet, people with low SES had a more unfavourable modifiable risk score suggesting more potential for lifestyle‐based interventions. LIBRA could be useful as a participant selection tool or as a surrogate outcome measure in lifestyle intervention trials, and can inform people about individual risk behaviours as part of public health initiatives.

Aim. To evaluate 10-year risk of potential development of type 2 diabetes (DM) in Russian population with the FINDRISC score, and to assess its associations with social, demographic and behavioral factors by the data from epidemiological study ESSE-RF. Material and methods. In the work, the data used, from multi-center study (Epidemiology of cardiovascular diseases in various regions of Russian Federation: ESSE-RF). Totally, 21923 persons investigated, age 25-64 y.o., of those 1045 (3,76% males, 5,39% females) had DM. To the final analysis 20878 persons included (8058 males, 12820 females) with no DM, for whom the 10-year risk was assessed with the FINDRISC (The FINnish Diabetes RIsk SCore). Level of risk and probability of DM onset were evaluated by the points summation. Also, associations were analyzed with education, marital status, place of inhabitance, income, smoking and alcohol status. Results. The threshold for high DM risk in Russian population was set at ≥12 level, with AUC 0,76, that represents good quality of model. The prevalence of the high risk by Russian criteria was 20,4%. Multifactorial analysis demonstrated that after correction for region and age, DM high risk was associated with smoking cessation (odds ratio (OR) 1,34; 95% confidence interval (CI) 1,14-1,58; р=0,0004) and alcohol consumption (OR 2,01; 95% CI 1,48-2,71; р=0,0001), and in women — with low income, low educational level and being married. Conclusion. Mean score by FINDRISC was 6,5±0,03, and absolute risk 5,3%. There were associations found of higher DM risk (≥12 points) with behavioral factors in males and social-demographic factors in women.

BackgroundHigh blood pressure (HBP) and diabetes mellitus (DM) are two of the most prevalent cardiometabolic disorders globally, especially among individuals with lower socio-economic status (SES). Studies have linked residential greenness to decreased risks of HBP and DM. However, there has been limited evidence on whether SES may modify the associations of residential greenness with HBP and DM.MethodsBased on a national representative cross-sectional study among 44,876 adults, we generated the normalized difference vegetation index (NDVI) at 1 km spatial resolution to characterize individuals’ residential greenness level. Administrative classification (urban/rural), nighttime light index (NLI), individual income, and educational levels were used to characterize regional urbanicity and individual SES levels.ResultsWe observed weaker inverse associations of NDVI with HBP and DM in rural regions compared to urban regions. For instance, along with per interquartile range (IQR, 0.26) increment in residential NDVI at 0∼5 year moving averages, the ORs of HBP were 1.04 (95%CI: 0.94, 1.15) in rural regions and 0.85 (95%CI: 0.79, 0.93) in urban regions (P = 0.003). Along with the decrease in NLI levels, there were continuously decreasing inverse associations of NDVI with DM prevalence (P for interaction <0.001). In addition, weaker inverse associations of residential NDVI with HBP and DM prevalence were found among individuals with lower income and lower education levels compared to their counterparts.ConclusionsLower regional urbanicity and individual SES could attenuate the associations of residential greenness with odds of HBP and DM prevalence.Supplementary informationThe online version contains supplementary material available at https://doi.org/10.1265/ehpm.24-00121.