Predictors of health-related quality of life in patients with non-communicable diseases: A national cross-section study

Al-Noumani, Huda; Alharrasi, Maryam; Zaabi, Omar Al; Natarajan, Jansirani

doi:10.1016/j.apnr.2022.151566

Cited by 3 publications

(4 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to WHO reports in 2020, NCDs were responsible for 82% of deaths in Iran, with cardiovascular diseases (CVD) and cancers being the leading causes, and these diseases accounted for 78.1% of the overall burden of diseases in the country 4 . NCDs result in reduced health‐related quality of life and increased financial strain 5,6 …”

Section: Introductionmentioning

confidence: 99%

“…4 NCDs result in reduced health-related quality of life and increased financial strain. 5,6 Estimates indicate that the aggregate cost attributed to the five primary NCDs-namely CVD, chronic respiratory disease, cancer, diabetes, and mental health conditions-is projected to amount to an astonishing sum of US$ 47 trillion during the period from 2010 to 2030. This equates to an average annual cost surpassing US$ 2 trillion.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Mouseli,

Sharafi,

Mastaneh

et al. 2023

Health Science Reports

View full text Add to dashboard Cite

BackgroundNoncommunicable diseases (NCDs) are the major causes of mortality across the globe, which impose a substantial burden on health care systems, particularly in low‐ and middle‐income countries. The present study aimed to determine socioeconomic inequality in the prevalence of NCDs using the concentration index (CI).MethodsThis cross‐sectional study was conducted on the baseline data of the Bandar Kong cohort. The principal component analysis was used to determine people's socioeconomic status (SES). The CI and Lorenz Curve were used for the assessment of socioeconomic inequality. Multivariate logistic regression was used to assess the relationship between SES and the prevalence of NCDs. A p Value less than 0.05 is considered significant.ResultsFrequency and prevalence of diabetes was 653 (16.22%), hypertension 848 (21.06%), chronic lung diseases 161 (4%), epilepsy 70 (1.74%), mental disorders 191 (4.74%), stillbirth 299 (13.94%), thyroid disorders 391 (9.71%) and depression 146 (3.63%). CI for the prevalence of diabetes was [−0.107, %95 CI: −0.146 to −0.068], hypertension [−0.122, %95 CI: −0.155 to −0.088], chronic lung disease [−0.116, %95 CI: −0.202 to −0.03], psychiatric disorders [−0.230, %95 CI: −0.304 to −0.155], depression [−0.132, %95 CI: −0.220 to−0.043] and stillbirth [−0.162, %95 CI: −0.220 to −0.105]. The Gini index was negative for all these diseases, indicating that these are significantly concentrated in people of poor SES.ConclusionsThe findings suggest that selected NCDs were concentrated among the poor and the low‐income. Particular attention may be necessary to address the problem of NCDs among these groups.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Mouseli,

Sharafi,

Mastaneh

et al. 2023

Health Science Reports

View full text Add to dashboard Cite

show abstract

“…Collectively these three health conditions account for 22 million deaths per year (Jagannathan et al, 2019; Khan et al, 2020; Soriano et al, 2020) and contribute to high healthcare expenditures (Muka et al, 2015). They may also decrease patients' mental health, social functioning and health‐related quality of life (Al‐Noumani et al, 2022; Van Wilder, 2022).…”

Section: Introductionmentioning

confidence: 99%

Records of quality indicators for management of long‐term health conditions of patients with intellectual disabilities in Dutch residential care

van den Bemd,

Suichies,

Bischoff

et al. 2023

Brit J Learn Disabil

View full text Add to dashboard Cite

BackgroundType 2 diabetes mellitus, cardiovascular disease and chronic obstructive pulmonary disease contribute significantly to societal and individual impact globally. High‐quality management of these long‐term health conditions is important to prevent deterioration of health, although potentially more complex for patients with intellectual disabilities in residential care. Disease management in this context particularly benefits from complete and accurate recording of disease management. Without complete records, long‐term health conditions are more difficult to track due to the level of uncertainty regarding which clinical examinations have and have not been performed. This study therefore aims to examine the recording routines of quality indicators for disease monitoring for chronically ill patients with intellectual disabilities in Dutch residential care.MethodsThis retrospective study utilised medical record data from a large Dutch long‐term care provider. We assessed the occurrence of cardiovascular disease (ICPC‐2 codes K74, K75, K76, K89 and K90), type 2 diabetes mellitus (T90, T90.02) and/or COPD (R91, R95). For adults with intellectual disabilities and long‐term condition, we analysed data entries in an 18‐month period (between July 2020 and December 2021). Observed consultation rates were calculated and presented in median with interquartile range and contrasted against the baseline number of consultations in primary care. Information on recorded quality indicators was presented in frequencies and percentages.FindingsOf the three long‐term conditions investigated, the most common was type 2 diabetes mellitus (8.6%; n = 287), followed by cardiovascular disease (5.8%; n = 195) and COPD (3.0%; n = 101). Of those who received management for their long‐term condition from their contracted GP, patients with type 2 diabetes mellitus, cardiovascular disease, or COPD had fewer consultations in 2021 than the Dutch baseline. Discussion of lifestyle was often not recorded. Disease monitoring quality indicators were recorded more often but at a lower frequency than expected.ConclusionsBecause of the infrequent recording of quality indicators, recording of management of long‐term conditions for patients with intellectual disabilities in long‐term care appears suboptimal. Although this may not directly harm individual patients, it may jeopardise the quality of management of long‐term conditions, as suboptimal recording limits opportunities for evaluation and improvement. Within a broader trend towards data‐driven work methods in healthcare, recording of quality indicators requires attention from practice, research and policy.

show abstract

“… 5 , 6 NCDs impact the daily life functioning of individuals reducing their quality of life and according to some estimates it accounts for 74% of global mortality. 7 The management of illness usually requires adherence to prescribed treatment as well as lifestyle changes. Patients are often required to undergo extensive medical examinations and compliance to treatment regimen to maintain health and functioning.…”

Section: Introductionmentioning

confidence: 99%

Quality of Life and Adherence to Healthcare Services During the COVID-19 Pandemic: A Cross-Sectional Analysis

Hassan¹,

Zahra²,

Parveen³

et al. 2022

PPA

View full text Add to dashboard Cite

Purpose To determine the relationship of various domains of quality of life (QoL) with healthcare adherence during the COVID-19 pandemic in Saudi Arabia. Methods The study sample comprised 795 participants among which 203 had a current diagnosis of any major NCDs, including cardiovascular diseases, diabetes mellitus, asthma, chronic pulmonary diseases, and chronic psychiatric illnesses and a control group of 592 participants who had no NCD. Participants completed an online survey questionnaire which obtained data on socio-demographic variables, types of NCDs, and healthcare adherence during the year 2020, the period during which Saudi Arabia underwent the first two waves of the COVID-19 pandemic. World Health Organization Quality of Life (WHOQOL-BREF) assessed the QoL in four domains physical, psychological, social and environmental and used standard scores in the analysis. GraphPad Prism 5 and SPSS 25V were employed for the statistical analysis. Bar graphs and frequency distribution tables present descriptive data. Bivariate and multivariate logistic regression analyses were computed to determine the significance of the relationship between QoL and healthcare adherence. Results Almost equal proportions of participants with NCDs (n=109/203; 54%) and without NCDs (n=327/592; 55%) demonstrated nonadherence to their regular healthcare during the COVID-19 pandemic (χ2=0.14; p=0.71). Patients with NCDs experienced lower quality of life in the psychological, social and environmental domains of QoL (p<0.05). Results from the multivariate regression analysis showed that female gender (AOR=1.52; p<0.05) psychological QoL (AOR=1.99; p<0.05), social QoL (AOR=1.98; p<0.05) and environmental QoL (AOR=1.95; p<0.05) significantly relate with adherence to healthcare. Conclusion Psychological, social and environmental may influence healthcare adherence among patients with NCDs during pandemics and should be focused on while devising future healthcare policy and interventions.

show abstract

Predictors of health-related quality of life in patients with non-communicable diseases: A national cross-section study

Cited by 3 publications

References 39 publications

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Contrasting socioeconomic inequality with noncommunicable diseases: Insights from a population‐based survey using the concentration index in Kong cohort study

Records of quality indicators for management of long‐term health conditions of patients with intellectual disabilities in Dutch residential care

Quality of Life and Adherence to Healthcare Services During the COVID-19 Pandemic: A Cross-Sectional Analysis

Contact Info

Product

Resources

About