Cardiometabolic multimorbidity and associated patterns of healthcare utilization and quality of life: Results from the Study on Global AGEing and Adult Health (SAGE) Wave 2 in Ghana.

Understanding the patterns of multimorbidity, defined as the co-occurrence of more than one chronic condition, is important for planning health system capacity and response. This study assessed the association of different cardiometabolic multimorbidity combinations with healthcare utilization and quality of life (QoL). Data were from the World Health Organization (WHO) study on global AGEing and adult health Wave 2 (2015) conducted in Ghana. We analysed the clustering of cardiometabolic diseases including angina, stroke, type 2 diabetes, and hypertension with unrelated conditions such as asthma, chronic lung disease, arthritis, cataract and depression. The clusters of adults with cardiometabolic multimorbidity were identified using latent class analysis and agglomerative hierarchical clustering algorithms. We used negative binomial regression to determine the association of multimorbidity combinations with outpatient visits. The association of multimorbidity clusters with hospitalization and QoL were assessed using multivariable logistic and linear regressions. Data from 3,128 adults aged over 50 years were analysed. We identified four distinct classes of multimorbidity: relatively "healthy class" with no multimorbidity (47.9%): abdominal obesity only (40.7%): cardiometabolic and arthritis class comprising participants with hypertension, type 2 diabetes, stroke, abdominal and general obesity, arthritis and cataract (5.7%); and cardiopulmonary and depression class including participants with angina, chronic lung disease, asthma, and depression (5.7%). Relative to the class with no multimorbidity, the cardiopulmonary and depression class was associated with a higher frequency of outpatient visits [ß = 0.3; 95% CI 0.1 to 0.6] and higher odds of hospitalization [aOR = 1.9; 95% CI 1.0 to 3.7]. However, cardiometabolic and arthritis class was associated with a higher frequency of outpatient visits [ß = 0.8; 95% CI 0.3 to 1.2] and not hospitalization [aOR = 1.1; 95% CI 0.5 to 2.9]. The mean QoL scores was lowest among participants in the cardiopulmonary and depression class [ß = -4.8; 95% CI -7.3 to -2.3] followed by the cardiometabolic and arthritis class [ß = -3.9; 95% CI -6.4 to -1.4]. Our findings show that cardiometabolic multimorbidity among older persons in Ghana cluster together in distinct patterns that differ in healthcare utilization. This evidence may be used in healthcare planning to optimize treatment and care.

Assessing the Readiness to Provide Integrated Management of Cardiovascular Diseases and Type 2 Diabetes in Kenya: Results from a National Survey.

Introduction: Integrated chronic disease management is the desired core function of a responsive healthcare system. However, many challenges surround its implementation in Sub-Saharan Africa. The current study assessed the readiness of healthcare facilities to provide integrated management of cardiovascular diseases (CVDs) and type 2 diabetes in Kenya. Methods: We used data from a nationally representative cross-sectional survey of 258 public and private health facilities conducted in Kenya between 2019 and 2020. Data were collected using a standardised facility assessment questionnaire and observation checklists modified from the World Health Organization Package of Essential Non-communicable Diseases. The primary outcome was the readiness to provide integrated care for CVDs and diabetes-defined as the mean availability of tracer items comprising trained staff and clinical guidelines, diagnostic equipment, essential medicines, diagnosis, treatment and follow-up. A cut-off threshold of ≥70% was used to classify facilities as 'ready'. Gardner-Altman plots and modified Poisson regression were used to examine the facility characteristics associated with care integration readiness. Results: Of the surveyed facilities, only a quarter (24.1%) were ready to provide integrated care for CVDs and type 2 diabetes. Care integration readiness was lower in public versus private facilities [aPR = 0.6; 95% CI 0.4 to 0.9], and primary healthcare facilities were less likely to be ready compared to hospitals [aPR = 0.2; 95% CI 0.1 to 0.4]. Facilities located in Central Kenya [aPR = 0.3; 95% CI 0.1 to 0.9], and the Rift Valley region [aPR = 0.4; 95% CI 0.1 to 0.9], were less likely to be ready compared to the capital Nairobi. Conclusions: There are gaps in the readiness of healthcare facilities particularly primary healthcare facilities in Kenya to provide integrated care services for CVDs and diabetes. Our findings inform the review of current supply-side interventions for integrated management of CVDs and type 2 diabetes, especially in lower-level public health facilities in Kenya.

Effect of Patient Support Groups for Hypertension on Blood Pressure among Patients with and Without Multimorbidity: Findings from a Cohort Study of Patients on a Home-Based Self-Management Program in Kenya.

Introduction: Patient support group interventions have been widely used to manage chronic diseases in Kenya. However, the potential benefits of these groups on patient health outcomes, and how this is influenced by multimorbidity, have not been rigorously evaluated. Objective: We assessed the effect of a patient support group intervention on blood pressure (BP) management and the potential moderating effect of multimorbidity among low- and middle-income patients with hypertension in Kenya. Methods: We analysed data from a non-randomized, quasi-experimental study of 410 patients with hypertension on a home-based self-management program conducted from September 2019 to September 2020. The program included the formation and participation in patient support groups. Using a modified STEPS questionnaire, data were collected on BP, anthropometry and other measurements at enrolment and after 12 months of follow-up. Multimorbidity was defined as the simultaneous presence of hypertension and at least one or more related conditions with similar pathophysiology (concordant multimorbidity) or unrelated chronic conditions (discordant multimorbidity). Propensity score (PS) weighting was used to adjust for baseline differences among 243 patients who participated in the support groups and 167 who did not. We estimated the effects of patient support groups and moderating effects of multimorbidity on BP management using multivariable ordinary linear regression weighted by PS. Findings: Participation in support groups significantly reduced systolic BP by 5.4 mmHg compared to non-participation in the groups [ß = -5.4; 95% CI -1.9 to -8.8]. However, among participants in the support group intervention, the mean systolic BP at follow-up assessment for those with concordant multimorbidity was 8.8 mmHg higher than those with no multimorbidity [ß = 8.8; 95% CI 0.8 to 16.8]. Conclusion: Although patient support groups are potentially important adjuncts to home-based self-care, multimorbidity attenuates their effectiveness. There is a need to tailor patient support group interventions to match the needs of the people living with multimorbidity in low- and middle-income settings in Kenya.

Cardiometabolic Multimorbidity Associated with Moderate and Severe Disabilities: Results from the Study on Global AGEing and Adult Health (SAGE) Wave 2 in Ghana and South Africa.

Background: Integrated management of cardiometabolic diseases is crucial in improving the quality of life of older persons. The objective of the study was to identify clusters of cardiometabolic multimorbidity associated with moderate and severe disabilities in Ghana and South Africa. Methods: Data were from the World Health Organization (WHO) study on global AGEing and adult health (SAGE) Wave-2 (2015) conducted in Ghana and South Africa. We analysed the clustering of cardiometabolic diseases including angina, stroke, diabetes, obesity, and hypertension with unrelated conditions such as asthma, chronic lung disease, arthritis, cataracts, and depression. The WHO Disability Assessment Instrument version 2.0 was used to assess functional disability. We used latent class analysis to calculate the multimorbidity classes and disability severity levels. Ordinal logistic regression was used to identify the clusters of multimorbidity associated with moderate and severe disabilities. Results: Data from 4,190 adults aged over 50 years were analysed. The prevalence of moderate and severe disabilities was 27.0% and 8.9% respectively. Four latent classes of multimorbidity were identified. These included a relatively healthy group with minimal cardiometabolic multimorbidity (63.5%), general and abdominal obesity (20.5%), hypertension, abdominal obesity, diabetes, cataracts, and arthritis (10.0%), and angina, chronic lung disease, asthma, and depression (6.0%). Compared to the participants with minimal cardiometabolic multimorbidity, the odds of moderate and severe disabilities were higher among participants with multimorbidity comprising hypertension, abdominal obesity, diabetes, cataract and arthritis [aOR = 3.0; 95% CI 1.6 to 5.6], and those with angina, chronic lung disease, asthma and depression [aOR = 2.7; 95% CI 1.6 to 4.5]. Conclusions: Cardiometabolic diseases among older persons in Ghana and South Africa cluster in distinct multimorbidity patterns that are significant predictors of functional disabilities. This evidence may be useful for defining disability prevention strategies and long-term care for older persons living with or at risk of cardiometabolic multimorbidity in sub-Saharan Africa.

Multimorbidity of cardiometabolic diseases: a cross-sectional study of patterns, clusters and associated risk factors in sub-Saharan Africa.

OBJECTIVE: To determine the patterns of cardiometabolic multimorbidity and associated risk factors in sub-Saharan Africa (SSA). DESIGN: We used data from the WHO STEPwise approach to non-communicable disease risk factor surveillance cross-sectional surveys conducted between 2014 and 2017. PARTICIPANTS: The participants comprised 39, 658 respondents aged 15-69 years randomly selected from nine SSA countries using a multistage stratified sampling design. PRIMARY OUTCOME MEASURE: Using latent class analysis and agglomerative hierarchical clustering algorithms, we analysed the clustering of cardiometabolic diseases (CMDs) including high blood sugar, hypercholesterolaemia, hypertension and cardiovascular diseases (CVDs) such as heart attack, angina and stroke. Clusters of lifestyle risk factors: harmful salt intake, physical inactivity, obesity, tobacco and alcohol use were also computed. Prevalence ratios (PR) from modified Poisson regression were used to assess the association of cardiometabolic multimorbidity with sociodemographic and lifestyle risk factors. RESULTS: Two distinct classes of CMDs were identified: relatively healthy group with minimal CMDs (95.2%) and cardiometabolic multimorbidity class comprising participants with high blood sugar, hypercholesterolaemia, hypertension and CVDs (4.8%). The clusters of lifestyle risk factors included alcohol, tobacco and harmful salt consumption (27.0%), and physical inactivity and obesity (5.8%). The cardiometabolic multimorbidity cluster exhibited unique sociodemographic and lifestyle risk profiles. Being female (PR=1.7, 95% CI (1.5 to 2.0), middle-aged (35-54 years) (3.9 (95% CI 3.2 to 4.8)), compared with age 15-34 years, employed (1.2 (95% CI 1.1 to 1.4)), having tertiary education (2.5 (95% CI 2.0 to 3.3)), vs no formal education and clustering of physical inactivity and obesity (2.4 (95% CI 2.0 to 2.8)) were associated with a higher likelihood of cardiometabolic multimorbidity. CONCLUSION: Our findings show that cardiometabolic multimorbidity and lifestyle risk factors cluster in distinct patterns with a disproportionate burden among women, middle-aged, persons in high socioeconomic positions, and those with sedentary lifestyles and obesity. These results provide insights for health systems response in SSA to focus on these clusters as potential targets for integrated care.

Readiness of health facilities to deliver non-communicable diseases services in Kenya: a national cross-sectional survey.

BACKGROUND: Non-communicable diseases (NCDs) account for an estimated 71% of all global deaths annually and nearly 80% of these deaths occur in low- and middle-income countries. This study aimed to assess the readiness of existing healthcare systems at different levels of health care in delivering NCDs management and prevention services in Kenya. METHODS: A cross-sectional survey of 258 facilities was conducted between June 2019 and December 2020 using multistage sampling, examining facility readiness based on the availability of indicators such as equipment, diagnostic capacity, medicines and commodities, trained staff and guidelines for NCDs management. Readiness scores were calculated as the mean availability of tracer items expressed as a percentage and a cut-off threshold of ≥ 70% was used to classify facilities as "ready" to manage NCDs. Descriptive and bivariate analyses were performed to assess the readiness of facilities by type, level, and location settings. Logistic regressions were used to identify factors associated with the readiness of facilities to provide disease-specific services. RESULTS: Of the surveyed facilities, 93.8% offered chronic respiratory disease (CRD) diagnosis and/or management services, 82.2% diabetes mellitus, 65.1% cardiovascular disease (CVD), and only 24.4% cervical cancer screening services. The mean readiness scores for diabetes mellitus (71%; 95% CI: 67-74) and CVD (69%; 95% CI: 66-72) were relatively high. Although CRD services were reportedly the most widely available, its mean readiness score was low (48%; 95% CI: 45-50). The majority of facilities offering cervical cancer services had all the necessary tracer items available to provide these services. Modeling results revealed that private facilities were more likely to be "ready" to offer NCDs services than public facilities. Similarly, hospitals were more likely "ready" to provide NCDs services than primary health facilities. These disparities in service readiness extended to the regional and urban/rural divide. CONCLUSIONS: Important gaps in the current readiness of facilities to manage NCDs in Kenya at different levels of health care were revealed, showing variations by disease and healthcare facility type. A collective approach is therefore needed to bridge the gap between resource availability and population healthcare needs.

Spatial and temporal inequalities in mortality in the USA, 1968-2016.

Previous UK and European research has highlighted important variations in mortality between populations after adjustment for key determinants such as poverty and deprivation. The aim here was to establish whether similar populations could be identified in the US, and to examine changes over time. We employed Poisson regression models to compare county-level mortality with national rates between 1968 and 2016, adjusting for poverty, education, race (a proxy for exposure to racism), population change and deindustrialisation. Results are presented by means of population-weighted cartograms, and highlight widening spatial inequalities in mortality over time, including an urban to rural, and south-westward, shift in areas with the highest levels of such unexplained 'excess' mortality. There is a need to understand the causes of the excess in affected communities, given that it persists after adjustment for such a broad range of important health determinants.

Theory driven analysis of social class and health outcomes using UK nationally representative longitudinal data.

BACKGROUND: Social class is frequently used as a means of ranking the population to expose inequalities in health, but less often as a means of understanding the social processes of causation. We explored how effectively different social class mechanisms could be measured by longitudinal cohort data and whether those measures were able to explain health outcomes. METHODS: Using a theoretically informed approach, we sought to map variables within the National Child Development Study (NCDS) to five different social class mechanisms: social background and early life circumstances; habitus and distinction; exploitation and domination; location within market relations; and power relations. Associations between the SF-36 physical, emotional and general health outcomes at age 50 years and the social class measures within NCDS were then assessed through separate multiple linear regression models. R2 values were used to quantify the proportion of variance in outcomes explained by the independent variables. RESULTS: We were able to map the NCDS variables to the each of the social class mechanisms except 'Power relations'. However, the success of the mapping varied across mechanisms. Furthermore, although relevant associations between exposures and outcomes were observed, the mapped NCDS variables explained little of the variation in health outcomes: for example, for physical functioning, the R2 values ranged from 0.04 to 0.10 across the four mechanisms we could map. CONCLUSIONS: This study has demonstrated both the potential and the limitations of available cohort studies in measuring aspects of social class theory. The relatively small amount of variation explained in the outcome variables in this study suggests that these are imperfect measures of the different social class mechanisms. However, the study lays an important foundation for further research to understand the complex interactions, at various life stages, between different aspects of social class and subsequent health outcomes.

Theorising social class and its application to the study of health inequalities.

The literature on health inequalities often uses measures of socio-economic position pragmatically to rank the population to describe inequalities in health rather than to understand social and economic relationships between groups. Theoretical considerations about the meaning of different measures, the social processes they describe, and how these might link to health are often limited. This paper builds upon Wright's synthesis of social class theories to propose a new integrated model for understanding social class as applied to health. This model incorporates several social class mechanisms: social background and early years' circumstances; Bourdieu's habitus and distinction; social closure and opportunity hoarding; Marxist conflict over production (domination and exploitation); and Weberian conflict over distribution. The importance of discrimination and prejudice in determining the opportunities for groups is also explicitly recognised, as is the relationship with health behaviours. In linking the different social class processes we have created an integrated theory of how and why social class causes inequalities in health. Further work is required to test this approach, to promote greater understanding of researchers of the social processes underlying different measures, and to understand how better and more comprehensive data on the range of social class processes these might be collected in the future.

Assessing the potential utility of commercial 'big data' for health research: Enhancing small-area deprivation measures with Experian™ Mosaic groups.

In contrast to area-based deprivation measures, commercial datasets remain infrequently used in health research and policy. Experian collates numerous commercial and administrative data sources to produce Mosaic groups which stratify households into 15 groups for marketing purposes. We assessed the potential utility of Mosaic groups for health research purposes by investigating their relationships with Indices of Multiple Deprivation (IMD) for the British population. Mosaic groups showed significant associations with IMD quintiles. Correspondence Analysis revealed variations in patterns of association, with Mosaic groups either showing increasing, decreasing, or some mixed trends with deprivation quintiles. These results suggest that Experian's Mosaics additionally measure other aspects of socioeconomic circumstances to those captured by deprivation measures. These commercial data may provide new insights into the social determinants of health at a small area level.

Dynamics of paediatric urogenital schistosome infection, morbidity and treatment: a longitudinal study among preschool children in Zimbabwe.

BACKGROUND: Recent research has shown that in schistosome-endemic areas preschool-aged children (PSAC), that is, ≤5 years, are at risk of infection. However, there exists a knowledge gap on the dynamics of infection and morbidity in this age group. In this study, we determined the incidence and dynamics of the first urogenital schistosome infections, morbidity and treatment in PSAC. METHODS: Children (6 months to 5 years) were recruited and followed up for 12 months. Baseline demographics, anthropometric and parasitology data were collected from 1502 children. Urinary morbidity was assessed by haematuria and growth-related morbidity was assessed using standard WHO anthropometric indices. Children negative for Schistosoma haematobium infection were followed up quarterly to determine infection and morbidity incidence. RESULTS: At baseline, the prevalence of S haematobium infection and microhaematuria was 8.5% and 8.6%, respectively. Based on different anthropometric indices, 2.2%-8.2% of children were malnourished, 10.1% underweight and 18.0% stunted. The fraction of morbidity attributable to schistosome infection was 92% for microhaematuria, 38% for stunting and malnutrition at 9%-34%, depending on indices used. S haematobium-positive children were at greater odds of presenting with microhaematuria (adjusted OR (AOR)=25.6; 95% CI 14.5 to 45.1) and stunting (AOR=1.7; 95% CI 1.1 to 2.7). Annual incidence of S haematobium infection and microhaematuria was 17.4% and 20.4%, respectively. Microhaematuria occurred within 3 months of first infection and resolved in a significant number of children, 12 weeks post-praziquantel treatment, from 42.3% to 10.3%; P<0.001. CONCLUSION: We demonstrated for the first time the incidence of schistosome infection in PSAC, along with microhaematuria, which appears within 3 months of first infection and resolves after praziquantel treatment. A proportion of stunting and malnutrition is attributable to S haematobium infection. The study adds scientific evidence to the calls for inclusion of PSAC in schistosome control programmes.

Comparative Assessment of Health Benefits of Praziquantel Treatment of Urogenital Schistosomiasis in Preschool and Primary School-Aged Children.

Schistosomiasis is a major public health problem in Africa. However, it is only recently that its burden has become recognised as a significant component impacting on the health and development of preschool-aged children. A longitudinal study was conducted in Zimbabwean children to determine the effect of single praziquantel treatment on Schistosoma haematobium-related morbidity markers: microhaematuria, proteinuria, and albuminuria. Changes in these indicators were compared in 1-5 years versus 6-10 years age groups to determine if treatment outcomes differed by age. Praziquantel was efficacious at reducing infection 12 weeks after treatment: cure rate = 94.6% (95% CI: 87.9-97.7%). Infection rates remained lower at 12 months after treatment compared to baseline in both age groups. Among treated children, the odds of morbidity at 12 weeks were significantly lower compared to baseline for proteinuria: odds ratio (OR) = 0.54 (95% CI: 0.31-0.95) and albuminuria: OR = 0.05 (95% CI: 0.02-0.14). Microhaematuria significantly reduced 12 months after treatment, and the effect of treatment did not differ by age group: OR = 0.97 (95% CI: 0.50-1.87). In conclusion, praziquantel treatment has health benefits in preschool-aged children exposed to S. haematobium and its efficacy on infection and morbidity is not age-dependent.

Identifying and evaluating field indicators of urogenital schistosomiasis-related morbidity in preschool-aged children.

BACKGROUND: Several studies have been conducted quantifying the impact of schistosome infections on health and development in school-aged children. In contrast, relatively little is known about morbidity levels in preschool-aged children (≤ 5 years) who have been neglected in terms of schistosome research and control. The aim of this study was to compare the utility of available point-of-care (POC) morbidity diagnostic tools in preschool versus primary school-aged children (6-10 years) and determine markers which can be used in the field to identify and quantify Schistosoma haematobium-related morbidity. METHODS/PRINCIPAL FINDINGS: A comparative cross-sectional study was conducted to evaluate the performance of currently available POC morbidity diagnostic tools on Zimbabwean children aged 1-5 years (n=104) and 6-10 years (n=194). Morbidity was determined using the POC diagnostics questionnaire-based reporting of haematuria and dysuria, clinical examination, urinalysis by dipsticks, and urine albumin-to-creatinine ratio (UACR). Attributable fractions were used to quantify the proportion of morbidity attributable to S. haematobium infection. Based on results of attributable fractions, UACR was identified as the most reliable tool for detecting schistosome-related morbidity, followed by dipsticks, visual urine inspection, questionnaires, and lastly clinical examination. The results of urine dipstick attributes showed that proteinuria and microhaematuria accounted for most differences between schistosome egg-positive and negative children (T=-50.1; p<0.001). These observations were consistent in preschool vs. primary school-aged children. CONCLUSIONS/SIGNIFICANCE: Preschool-aged children in endemic areas can be effectively screened for schistosome-related morbidity using the same currently available diagnostic tools applicable to older children. UACR for detecting albuminuria is recommended as the best choice for rapid assessment of morbidity attributed to S. haematobium infection in children in the field. The use of dipstick microhaematuria and proteinuria as additional indicators of schistosome-related morbidity would improve the estimation of disease burden in young children.

Variability of patient safety culture in Belgian acute hospitals.

OBJECTIVES: The aim of this study was to measure differences in safety culture perceptions within Belgian acute hospitals and to examine variability based on language, work area, staff position, and work experience. METHODS: The Hospital Survey on Patient Safety Culture was distributed to hospitals participating in the national quality and safety program (2007-2009). Hospitals were invited to participate in a comparative study. Data of 47,136 respondents from 89 acute hospitals were used for quantitative analysis. Percentages of positive response were calculated on 12 dimensions. Generalized estimating equations models were fitted to explore differences in safety culture. RESULTS: Handoffs and transitions, staffing, and management support for patient safety were considered as major problem areas. Dutch-speaking hospitals had higher odds of positive perceptions for most dimensions in comparison with French-speaking hospitals. Safety culture scores were more positive for respondents working in pediatrics, psychiatry, and rehabilitation compared with the emergency department, operating theater, and multiple hospital units. We found an important gap in safety culture perceptions between leaders and assistants within disciplines. Administration and middle management had lower perceptions toward patient safety. Respondents working less than 1 year in the current hospital had more positive safety culture perceptions in comparison with all other respondents. CONCLUSIONS: Large comparative databases provide the opportunity to identify distinct high and low scoring groups. In our study, language, work area, and profession were identified as important safety culture predictors. Years of experience in the hospital had only a small effect on safety culture perceptions.

Comparing parasitological vs serological determination of Schistosoma haematobium infection prevalence in preschool and primary school-aged children: implications for control programmes.

To combat schistosomiasis, the World Health Organization (WHO) recommends that infection levels are determined prior to designing and implementing control programmes, as the treatment regimens depend on the population infection prevalence. However, the sensitivity of the parasitological infection diagnostic method is less reliable when infection levels are low. The aim of this study was to compare levels of Schistosoma haematobium infection obtained by the parasitological method vs serological technique. Infection levels in preschool and primary school-aged children and their implications for control programmes were also investigated. Infection prevalence based on serology was significantly higher compared with that based on parasitology for both age groups. The difference between infection levels obtained using the two methods increased with age. Consequentially, in line with the WHO guidelines, the serological method suggested a more frequent treatment regimen for this population compared with that implied by the parasitological method. These findings highlighted the presence of infection in children aged ⩽5 years, further reiterating the need for their inclusion in control programmes. Furthermore, this study demonstrated the importance of using sensitive diagnostic methods as this has implications on the required intervention controls for the population.

Influence of chronic comorbidity and medication on the efficacy of treatment in patients with diabetes in general practice.

BACKGROUND: Evidence on the influence of comorbidity and comedication on clinical outcomes in patients with type 2 diabetes mellitus is scarce. AIM: To ascertain the effect of five chronic diseases (joint disorder, respiratory disease, anaemia, malignancy, depression) and three chronically used drugs (non-steroid anti-inflammatory drugs [NSAIDs], corticosteroids, antidepressants) on treatment for hypoglycaemia in patients with type 2 diabetes. DESIGN AND SETTING: Retrospective cohort study in a variety of practices across Flanders, Belgium. METHOD: A retrospective cohort study was conducted, based on data from Intego, a general practice-based continuous morbidity registry. Multiple logistic regression analysis was used to predict the change in glycosylated haemoglobin (HbA1c) levels related to comorbidity, comedication, and a combination of both in 3416 patients with type 2 diabetes. Adjustments were made for age, sex, and diabetes-treatment group (diet, oral antidiabetic drugs, combination treatment, insulin). RESULTS: Concomitant joint and respiratory disorders, as well as the chronic use of NSAIDs and corticosteroids, either separately or in combination, were significantly associated with the worsening of HbA1c levels. Anaemia, depression, malignancy, and antidepressants had no statistically significant influence on the efficacy of treatment for hypoglycaemia. CONCLUSION: The presence of some comorbid diseases or drug use can impede the efficacy of treatment for type 2 diabetes. This finding supports the need to develop treatment recommendations, taking into account the presence of both chronic comorbidity and comedication. Further research must be undertaken to ascertain the effect other combinations of chronic diseases have on the efficacy of treatment of this and other diseases.