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Andrea Dell’Isola, Ali Kiadaliri, Clara Hellberg, Aleksandra Turkiewicz, Martin Englund Clinical Epidemiology Unit, Department of Clinical Sciences Lund, Orthopedics, Lund University, Lund, SwedenCorrespondence: Andrea Dell’Isola, Email andrea.dellisola@med.lu.sePurpose: (i) To report the prevalence of participants to a first-line intervention for OA in Sweden using over-the-counter (OTC) and/or prescribed NSAIDs; (ii) To estimate the accuracy of dispensed prescriptions of NSAIDs recorded in a Swedish health-care register to capture the use of NSAID considering clinician-report as reference standard.Methods: Register-based study. We used data from OA individuals who participated in the Swedish first-line intervention recorded in the Swedish Osteoarthritis Register (SOAR). SOAR includes clinician-reported use of NSAIDs in the three months preceding the intervention. We used the Prescribed Drug Register to retrieve data on NSAID prescriptions dispensed in the same period. We estimated the prevalence of OTC users (individuals with clinicians-reported use of NSAID but no prescription dispensed), prescription users (individuals with clinicians-reported use of NSAID and a prescription dispensed) and non-users (neither of the previous). We calculated sensitivity, specificity, positive predictive value, and negative predictive value of dispensed prescriptions of NSAIDs vs clinician-report.Results: We included 116,162 individuals (mean age [Standard Deviation]: 66 [9.6] years, 79% women, 77% knee OA). Overall, 24.7% (95% Confidence Intervals [CI] 24.5%; 25.0%) used OTC NSAIDs only, 18.2% (18.0%; 18.5%) used prescribed NSAIDs, 6.6% (6– 4%; 6.7%) reported not using NSAIDs while having an NSAID prescription dispensed. Of the 49,913 individuals with clinician-reported use of NSAIDs, 21,190 had a prescription dispensed (sensitivity: 42.5% [95% CI 42.0%, 42.9%]; positive predictive value: 73.5% [73.0%, 74.0%]). Of the 66,249 individuals reporting not using NSAIDs, 58,617 did not have a prescription dispensed (specificity: 88.5% [88.2%, 88.7%]; negative predictive value: 67.1% [66.8%, 67.4%]).Conclusion: Overall, 24.7% of participants in a first-line intervention for OA used OTC NSAIDs only while 18.2% used prescribed NSAIDs. Dispensed prescriptions of NSAIDs have high specificity but low sensitivity and can correctly identify about 70% of both the non-users and users in this population.Keywords: osteoarthritis, NSAID, register, validation

Objective To investigate the associations between rheumatic and musculoskeletal diseases (RMDs) and incident dementia using population register‐based data. Methods This nested case‐control study was conducted based on a cohort of residents in the Skåne region, Sweden, aged 50 years and older in 2009 without doctor‐diagnosed dementia during 1998 to 2009 (n = 402,825). Individuals with a new main diagnosis of dementia during 2010 to 2019 were identified as incident patients with dementia (n = 22,131). Controls without diagnosed dementia were randomly matched 1:1 by sex, age, and Elixhauser comorbidity index using incidence density sampling. Separate conditional logistic regression analyses adjusted for confounders were fitted for the following RMDs, diagnosed at least 2 years before dementia diagnosis as exposure: gout, osteoarthritis, rheumatoid arthritis, spondyloarthropathies (SpA), and systemic connective tissue disorders. Subgroup analyses by dementia subtype, sex, age, comorbidity, and RMDs/dementia identification were conducted. Results Although gout (adjusted rate ratio 0.88; 95% confidence interval 0.79–0.97), osteoarthritis (0.92; 0.88–0.96), and systemic connective tissue disorders (0.91; 0.83–0.99) were associated with decreased risk of dementia, the associations for rheumatoid arthritis (1.05; 0.92–1.19) and SpA (1.17; 0.94–1.45) were inconclusive. The associations between RMDs and incident dementia were similar across sex, age, and comorbidity subgroups with a few exceptions (eg, an adjusted rate ratio of 0.99 [95% confidence interval 0.71–1.39] in males vs 1.31 [0.99–1.74] in female patients for SpA). Conclusion Persons with diagnosed RMDs seem to have comparable or slightly lower risks of developing dementia compared with those without known RMD.

The aim of this study was to map and model the noise pollution level (NPL) of a highway in Iran by using statistical techniques, geographic information system (GIS) Software, and the Traffic Noise Model version 2.5 (TNM2.5). The equivalent noise level in A weighting network (L eq(A)) was measured in 28 stations in different seasons using the sound level meter of the TES-1358 model. The traffic noise data and indices L eq (equivalent noise level), L max and L min (the maximum and minimum time-weighted noise levels), L n (noise pressure level exceeded for n percent of the time), NPL, and TNI (traffic noise index) were measured and calculated to determine the daily sound level. They were then statistically analyzed by SPSS and Sigma Plot Software. Finally, the GIS software and TNM2.5 techniques were used to map and predict the traffic NPL in the region and the distribution of noise levels. The highest noise level was measured at about 80 and 79.61 dB in Kouhsangi and Abadgaran stations, respectively. The lowest level was measured at around 58 dB in the Hafez Square station. In addition, the results show that the highest and lowest L eq were almost in the same range (81–85 dB). It appears that the TNM2.5 model can reasonably predict traffic noise levels as well as the dispersion and nature of noise pollution on the highway.

Objective: To examine changes in prevalence and socioeconomic inequalities in knee and hip OA outcomes, in more specific surgery and non-surgery specialist care visits, from 2001 to 2011 in Sweden and to what extent sociodemographic factors can explain the changes. Design: We included all individuals aged ≥35 years resident in Sweden from 2001 to 2011. Individual-level data was retrieved from the Swedish Interdisciplinary Panel. Highest educational attainment was used as socioeconomic measure and the concentration index was used to assess relative and absolute educational inequalities. We used decomposition method to examine changes in prevalence and relative educational inequalities. Results: A total of 4,794,693 and 5,359,186 people were included for the years 2001 and 2011, respectively. The crude prevalence of surgery and specialist visits for knee and hip OA was 36–83% higher in 2011 than in 2001. The increase in hip OA outcomes was largely explained by changes in the sociodemographic composition of the population, whereas for knee OA outcomes, changes in the strength of the associations with sociodemographic factors appeared more important. All outcomes were concentrated among people with lower education in all study years. The relative inequalities declined over the study period, while the absolute inequalities increased for knee OA outcomes and remained stable for hip OA. Conclusion: Our findings show an increasing burden of all studied OA outcomes. Moreover, our findings suggest persistent educational inequalities with more surgeries and specialist visits among lower-educated individuals. Future research should incorporate additional variables to better understand and address these inequalities.

Objectives To identify multimorbidity trajectories over 20 years among incident osteoarthritis (OA) individuals and OA-free matched references.Methods Cohort study using prospectively collected healthcare data from the Skåne region, Sweden (~1.4 million residents). We extracted diagnoses for OA and 67 common chronic conditions. We included individuals aged 40+ years on 31 December 2007, with incident OA between 2008 and 2009. We selected references without OA, matched on birth year, sex, and year of death or moving outside the region. We employed group-based trajectory modelling to capture morbidity count trajectories from 1998 to 2019. Individuals without any comorbidity were included as a reference group but were not included in the model.Results We identified 9846 OA cases (mean age: 65.9 (SD 11.7), female: 58%) and 9846 matched references. Among both cases and references, 1296 individuals did not develop chronic conditions (no-chronic-condition class). We identified four classes. At the study outset, all classes exhibited a low average number of chronic conditions (≤1). Class 1 had the slowest progression towards multimorbidity, which increased progressively in each class. Class 1 had the lowest count of chronic conditions at the end of the follow-up (mean: 2.9 (SD 1.7)), while class 4 had the highest (9.6 (2.6)). The presence of OA was associated with a 1.29 (1.12, 1.48) adjusted relative risk of belonging to class 1 up to 2.45 (2.12, 2.83) for class 4.Conclusions Our findings suggest that individuals with OA face an almost threefold higher risk of developing severe multimorbidity.

This study presents the Modified Bare Soil Index (MBI), an innovative remote sensing instrument that employs Short Wave Infrared (SWIR) and Near Infrared (NIR) wavelengths sourced from Landsat 8 satellite observations. Its purpose is to refine the identification and distinction of bare soil within woodland regions. Addressing the limitations of existing methods, MBI represents a significant advancement in land cover change detection. Through a focused study in the Sardasht forests of western Iran, the MBI demonstrates superior accuracy, achieving an overall accuracy of approximately 96 % with a Kappa coefficient exceeding 0.94, surpassing traditional bare soil indices. This innovation improves the classification of land surfaces and also aids in the efficient monitoring and safeguarding of changes in land cover. The MBI's robust performance underscores its potential in smart forestry, enabling more precise identification and surveillance of bare soil areas. This advancement is pivotal for ecological studies and resource management, offering a practical solution to the challenges of soil erosion and land degradation. By integrating advanced spectral analysis with satellite imagery, the MBI sets a new standard in remote sensing techniques, offering vital insights for environmental conservation and agricultural practices.

Objective: To explore sex and age differences in Patient-Reported Outcomes Measures (PROMs) and adherence to digital osteoarthritis (OA) self-management intervention. Methods: A register-based study with data from an OA digital self-management intervention. PROMs and adherence were collected at baseline and/or 3 ​month follow-up: ‘pain intensity’ in hip/knee (best/worst: 0–10), ‘activity impairments' (best/worst: 0–10), ‘overall health’ perception (worst/best: 0–10), ‘physical function’ (30-s chair stand test), ‘health-related quality of life’ (EQ-5D-5L index score; worst/best: 0.243–0.976), the subscales and total scores of the Knee Injury/Hip Disability and Osteoarthritis Outcome Score (KOOS/HOOS-12; worst/best: 0–100), ‘fear of movement’ (yes/no), ‘walking difficulties' (yes/no), ‘programme adherence’ (0–100 ​% and ≥80 ​% [yes/no]), ‘patient acceptable symptom state’ (PASS; yes/no), and ‘treatment failure’ (those who answered no to PASS question and thought the treatment failed [yes/no]). We used linear/logistic regression to calculate mean/risk differences in the PROMs and adherence levels among sex and age groups at 3-month follow-up. We employed entropy balancing to explore the contributions of baseline characteristics and different covariates to the sex/age differences. Results: We included 14,610 participants (mean (SD) age: 64.1 (9.1), 75.5 ​% females). Females generally reported better outcomes than males. Participants aged ≥70 had greater activity impairments, lower KOOS/HOOS-pain/function scores, more walking difficulties, less fear of movement and higher adherence than those

In the aerial images taken from the forests, the crowns of the trees are recorded. Using DN, texture and crown pattern, the type of trees can be predicted with a certain accuracy and used in forest studies. DN is the amount of light intensity that assigns a number to each component of digital images depending on the number of image bits. The presence of foliage causes the space under the canopy to be affected by shade and semi-shade, and these areas have close to zero DNs. The canopy of trees has less effect on aerial images in autumn and winter, but the need to study the forest throughout the year, in spring and summer will be a problem. On the other hand, some LIDAR and RADAR sensors have the ability to pass through the canopy of trees, but these sensors are not always available and their imaging cost is higher than UAVs that capture in the visible range. The need to use image processing methods is to be able to prevent the loss of information about the crown of trees in visible aerial images, and to extract information about the areas affected by the shadow and semi-shadow of the crown for interpretation. Due to the 8-bit image, in this research, 8 level of transfer have been done. At each step of the transition, the DN of each pixel is compared with the average DN of the image. DNs that are larger than the average are assigned a value of 1 and other DNs are assigned a value of 0. The output of this step is an image with an 8-digit binary number assigned to each pixel. By converting the binary number to decimal, the DNs of the image are reconstructed and the image is improved. Due to the increased structural similarity of the fused image (0.8762) compared to the original image (0.2783), we expect the image to improve. In the second step, the transferred pixels are multiplied by the new mean and then subtracted from the value of the old DNs. This creates an image where the tree trunks are dark and other parts of the image are light. In the next step, we open and close the image. This operation consists of two stages: Erosion and Dilation. Erosion is performed on a binary image and the remaining parts of the crown are shortened or thinned. This morphological operation works evenly on the whole image and makes the trunks of the trees thinner, so the Dilation operation is applied to remove the spots created in the image, creating large small gaps between the crown The trees are shown in the picture, which shows the trunks of the trees. Finally, by forming a graph between the trees, the distances between them are calculated in terms of pixels of the image.

Abstract Background Healthcare system and intersectoral public health policies play a crucial role in improving population health and reducing health inequalities. This study aimed to quantify their impact, operationalized as avoidable deaths, on the gap in life expectancy (LE) and lifespan inequality (LI) between Iran and three neighbour countries viz., Turkey, Qatar, and Kuwait in 2015–2016. Methods Annual data on population and causes of deaths by age and sex for Iran and three neighbour countries were obtained from the World Health Organization mortality database for the period 2015–2016. A recently developed list by the OECD/Eurostat was used to identify avoidable causes of death (with an upper age limit of 75). The cross-country gaps in LE and LI (measured by standard deviation) were decomposed by age and cause of death using a continuous-change model. Results Iranian males and females had the second lowest and lowest LE, respectively, compared with their counterparts in the neighbour countries. On the other hand, the highest LIs in both sexes (by 2.3 to 4.5 years in males and 1.1 to 3.3 years in females) were observed in Iran. Avoidable causes contributed substantially to the LE and LI gap in both sexes with injuries and maternal/infant mortality represented the greatest contributions to the disadvantages in Iranian males and females, respectively. Conclusions Higher mortality rates in young Iranians led to a double burden of inequality –shorter LE and greater uncertainty at timing of death. Strengthening intersectoral public health policies and healthcare quality targeted at averting premature deaths, especially from injuries among younger people, can mitigate this double burden.

Iranian mangrove forests provides valuable information to prevent genetic erosion in the gene pool of these ecosystems. The aim of this study was to investigate the genetic diversity among mangrove forests located in four different regions of Iran, based on morphological characteristics and microsatellite markers. Cluster analysis of molecular data, using neighbor joining algorithm classified the 60 mangrove trees, sampled from different coastal areas, into four groups. Analysis of molecular variance showed that the majority (77%) of the variance explained by among-population variation and the highest values of genetic diversity parameters including number of effective alleles, Shannon’s information index, and Nei’s genetic diversity were obtained for the Qeshm population, indicating that region is the most diverse population among all the studied populations. Baced on the morphological analyses significant differences were observed between all populations in terms of height, diameter at breast height, collar diameter, leaf size, pneumatophore length and pneumatophore diameter. The present study, provides useful information about genetic diversity of mangrove habitats which can be used in evolutionary studies and conservation efforts for these valuable plant ecosystems.

To investigate how the co-occurrence of diabetes, hypertension and overweight/obesity is associated with pain following an exercise intervention for knee and hip osteoarthritis (OA). Register-based cohort study. We included people from the Swedish Osteoarthritis Register who underwent education and exercise for knee or hip OA. Diabetes and hypertension were defined using medical records and dispensation of medication. Body Mass Index (BMI) was used to identify people with overweight (≥25 to <30), and obesity (≥30). We used linear mixed-effect models with patients nested into clinics to estimate the associations between the exposures and pain (Numeric Rating Scale 0–10), adjusting for age, sex, education, and physical activity. We analysed 80,893 patients with knee or hip OA. The accumulation of metabolic conditions was associated with worse pain at baseline and follow-ups. When obesity, hypertension and diabetes coexisted, patients treated for knee OA reported more pain at baseline (adjusted mean pain difference 0.9 [95 %CI: 0.8; 1.0]), 3 months (1.0 [0.9; 1.1]) and 12 months (1.3 [1.1; 1.4]) compared to those without any of the conditions. Similar results were observed for patients treated for hip OA when obesity, hypertension and diabetes coexisted (baseline (0.7 [0.5; 0.8], 3 (0.8[0.6; 1.0]) and 12 months (1.1[0.8; 1.3]). When diabetes, hypertension and obesity coexist with OA, patients not only experience heightened baseline pain compared to metabolically healthy individuals, but the disparity increases after an education and exercise intervention suggesting that a one-size-fits-all approach may be inadequate in addressing the complex interplay between metabolic health and OA. [ABSTRACT FROM AUTHOR]

BackgroundA key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016.MethodsDrawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita.FindingsIn 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8-98·1) in Iceland, followed by 96·6 (94·9-97·9) in Norway and 96·1 (94·5-97·3) in the Netherlands, to values as low as 18·6 (13·1-24·4) in the Central African Republic, 19·0 (14·3-23·7) in Somalia, and 23·4 (20·2-26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1-93·6) in Beijing to 48·0 (43·4-53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6-68·8) in Goa to 34·0 (30·3-38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries.InterpretationGBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view-and subsequent provision-of quality health care for all populations.FundingBill & Melinda Gates Foundation.

BackgroundThe UN's Sustainable Development Goals (SDGs) are grounded in the global ambition of "leaving no one behind". Understanding today's gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990-2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030.MethodsWe used standardised GBD 2016 methods to measure 37 health-related indicators from 1990 to 2016, an increase of four indicators since GBD 2015. We substantially revised the universal health coverage (UHC) measure, which focuses on coverage of essential health services, to also represent personal health-care access and quality for several non-communicable diseases. We transformed each indicator on a scale of 0-100, with 0 as the 2·5th percentile estimated between 1990 and 2030, and 100 as the 97·5th percentile during that time. An index representing all 37 health-related SDG indicators was constructed by taking the geometric mean of scaled indicators by target. On the basis of past trends, we produced projections of indicator values, using a weighted average of the indicator and country-specific annualised rates of change from 1990 to 2016 with weights for each annual rate of change based on out-of-sample validity. 24 of the currently measured health-related SDG indicators have defined SDG targets, against which we assessed attainment.FindingsGlobally, the median health-related SDG index was 56·7 (IQR 31·9-66·8) in 2016 and country-level performance markedly varied, with Singapore (86·8, 95% uncertainty interval 84·6-88·9), Iceland (86·0, 84·1-87·6), and Sweden (85·6, 81·8-87·8) having the highest levels in 2016 and Afghanistan (10·9, 9·6-11·9), the Central African Republic (11·0, 8·8-13·8), and Somalia (11·3, 9·5-13·1) recording the lowest. Between 2000 and 2016, notable improvements in the UHC index were achieved by several countries, including Cambodia, Rwanda, Equatorial Guinea, Laos, Turkey, and China; however, a number of countries, such as Lesotho and the Central African Republic, but also high-income countries, such as the USA, showed minimal gains. Based on projections of past trends, the median number of SDG targets attained in 2030 was five (IQR 2-8) of the 24 defined targets currently measured. Globally, projected target attainment considerably varied by SDG indicator, ranging from more than 60% of countries projected to reach targets for under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria, to less than 5% of countries projected to achieve targets linked to 11 indicator targets, including those for childhood overweight, tuberculosis, and road injury mortality. For several of the health-related SDGs, meeting defined targets hinges upon substantially faster progress than what most countries have achieved in the past.InterpretationGBD 2016 provides an updated and expanded evidence base on where the world currently stands in terms of the health-related SDGs. Our improved measure of UHC offers a basis to monitor the expansion of health services necessary to meet the SDGs. Based on past rates of progress, many places are facing challenges in meeting defined health-related SDG targets, particularly among countries that are the worst off. In view of the early stages of SDG implementation, however, opportunity remains to take actions to accelerate progress, as shown by the catalytic effects of adopting the Millennium Development Goals after 2000. With the SDGs' broader, bolder development agenda, multisectoral commitments and investments are vital to make the health-related SDGs within reach of all populations.FundingBill & Melinda Gates Foundation.

Objective: To investigate whether the first wave of the COVID-19 pandemic impacted healthcare consultations (HCC) and hospitalization among people with and without osteoarthritis (OA). Methods: Using register data, we included individuals aged ≥35 years residing in Skåne region, Sweden, during 2009–2019 with (n ​= ​123,523) and without (n ​= ​552,412) a diagnosis of OA during January 1, 2009–December 31, 2019. We collected bi-weekly individual data on HCC/hospitalization between January and May for years 2017–2020. Treating the year 2020 as intervention and 2017–2019 as control as well as dividing data to pre– (January–February) and post–pandemic (March–May), we applied event study design to measure the dynamic effects of the COVID-19 pandemic on HCC/hospitalization. We used fixed-effect Poisson regressions for estimation and subgroup analyses by sex, age, and comorbidity were conducted among OA patients. Results: The impact of the pandemic on healthcare use was evident from mid-March 2020 (34–45%/12–25% reductions in in-person HCC/hospitalization) among people with OA relative to 2017–2019. Smaller reductions were seen in those without OA with 25–34%/8–16% reductions in in-person HCC/hospitalization. On contrary, there were increases in remote HCC following the pandemic (5–25% and 11–31% in people with and without OA, respectively). Among persons with OA, there were variations in the pandemic's effects by sex, age and comorbidity. Conclusion: Despite no lockdown in Sweden there were substantial reductions in in-person healthcare use during the first wave of COVID-19 pandemic with greater reductions among people with than without OA.