Demographic and socioeconomic inequalities in oral healthcare utilisation in Malaysia: evidence from a national survey

Tan, Yeung R’ong; Tan, Ee Hong; Jawahir, Suhana; Hanafiah, Ainul Nadziha Mohd; Yunos, Muhammad Hafiz Mohd

doi:10.1186/s12903-020-01388-w

Cited by 19 publications

(23 citation statements)

References 50 publications

(60 reference statements)

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“…This can result in inaccurate estimates of standard errors, p-values, and confidence intervals. However, a recently published local study [21] of oral healthcare has taken measures to limit the data analysis for one visit and make the assumption that zero occurrences are true zero.…”

Section: Discussionmentioning

confidence: 99%

“…Statistical analysis was performed using STATA 14 (Stata Corporation, College Station, TX). The 'svyset' command were used and weight estimation for the complex survey design based on the probability of sampling, the non-response and post-stratification adjustment by ethnicity, age, and gender [21].…”

Section: Theoretical Approaches and Studied Variablesmentioning

confidence: 99%

“…OLS is a common and basic form of regression with a distinct assumption of normality. The most common evidence published using this National Health Morbidity dataset uses OLS for the analysis of continuous outcome variables [21]. However, with the healthcare utilisation concept, Poisson regression, a basic count model, is used.…”

Section: Comparison Of Regression Modelsmentioning

confidence: 99%

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Count data models for outpatient health services utilisation

Bakar

Hamid

Sham

et al. 2022

BMC Med Res Methodol

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Background Count data from the national survey captures healthcare utilisation within a specific reference period, resulting in excess zeros and skewed positive tails. Often, it is modelled using count data models. This study aims to identify the best-fitting model for outpatient healthcare utilisation using data from the Malaysian National Health and Morbidity Survey 2019 (NHMS 2019) and utilisation factors among adults in Malaysia. Methods The frequency of outpatient visits is the dependent variable, and instrumental variable selection is based on Andersen’s model. Six different models were used: ordinary least squares (OLS), Poisson regression, negative binomial regression (NB), inflated models: zero-inflated Poisson, marginalized-zero-inflated negative binomial (MZINB), and hurdle model. Identification of the best-fitting model was based on model selection criteria, goodness-of-fit and statistical test of the factors associated with outpatient visits. Results The frequency of zero was 90%. Of the sample, 8.35% of adults utilized healthcare services only once, and 1.04% utilized them twice. The mean-variance value varied between 0.14 and 0.39. Across six models, the zero-inflated model (ZIM) possesses the smallest log-likelihood, Akaike information criterion, Bayesian information criterion, and a positive Vuong corrected value. Fourteen instrumental variables, five predisposing factors, six enablers, and three need factors were identified. Data overdispersion is characterized by excess zeros, a large mean to variance value, and skewed positive tails. We assumed frequency and true zeros throughout the study reference period. ZIM is the best-fitting model based on the model selection criteria, smallest Root Mean Square Error (RMSE) and higher R2. Both Vuong corrected and uncorrected values with different Stata commands yielded positive values with small differences. Conclusion State as a place of residence, ethnicity, household income quintile, and health needs were significantly associated with healthcare utilisation. Our findings suggest using ZIM over traditional OLS. This study encourages the use of this count data model as it has a better fit, is easy to interpret, and has appropriate assumptions based on the survey methodology.

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Section: Discussionmentioning

confidence: 99%

Section: Theoretical Approaches and Studied Variablesmentioning

confidence: 99%

Section: Comparison Of Regression Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Count data models for outpatient health services utilisation

Bakar

Hamid

Sham

et al. 2022

BMC Med Res Methodol

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“…Locally, periodontal disease prevalence declined between 1990 (92.8%) and 2000 (87.2%); however, a sharp rise was observed in the 2010 National Oral Health Survey for Adults (NOHSA) (94.0%) [ 6 , 7 ]. The extremely high prevalence of periodontitis among adults is also challenged by the poor oral healthcare utilisation practices among Malaysian adults where only 13.2% reportedly saw a dentist within the last 12 months as highlighted in the National Health and Morbidity Survey in 2019 [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Aziz

Dom

Mustafa

et al. 2022

BMC Health Serv Res

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Background The practice of referring diabetic patients for dental intervention has been poor despite awareness and knowledge of the oral health effects of diabetes. Likewise, dentists treating patients receiving diabetes treatment are rarely updated on the glycaemic status and as a result, the opportunity for shared management of these patients is missed. This study aimed to provide a standardised care pathway which will initiate screening for diabetes from dental clinics and link patients with primary care for them to receive optimised care for glycaemic control. Method A Modified Delphi technique was employed to obtain consensus on recommendations, based on current evidence and best care practices to screen for diabetes among patients attending dental clinics for periodontitis. Expert panel members were recruited using snowball technique where the experts comprised Family Medicine Specialists (5), Periodontists (6), Endocrinologists (3) and Clinical Pharmacists (4) who are involved in management of patients with diabetes at public and private healthcare facilities. Care algorithms were designed based on existing public healthcare services. Results The CODAPT© panel recommends referral to primary care for further evaluation of glycaemic status if patients diagnosed with periodontitis record fasting capillary blood glucose levels ≥ 5.6 mmol/L. Intervention treatment options for prediabetes are listed, and emphasis on feedback to the dental healthcare team is outlined specifically. Conclusion The CODAPT© care pathway has the potential to link dental clinics with primary care for diagnosis and/or optimised treatment of prediabetes/diabetes among patients receiving periodontitis treatment.

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“…The overall dental health of Malaysians and their utilization of dental care facilities was recently reported in a national survey [ 14 ]. However, the impact of dental health on OHRQoL amongst different ethnicities in Malaysia remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Validation of the Malay Oral Impacts on Daily Performances and Evaluation of Oral Health-Related Quality of Life in a Multi-Ethnic Urban Malaysian Population: A Cross-Sectional Study

Lim

Goo

Leung

et al. 2022

IJERPH

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Oral Impacts on Daily Performances (OIDP) can be used as a generic or condition-specific oral health-related quality of life (OHRQoL) instrument. It offers different contexts on how dental conditions affect OHRQoL. This cross-sectional study aimed to validate a newly translated Malay OIDP (OIDP-M), compare OHRQoL, decayed, missing, or filled teeth (DMFT) in Malaysians, and investigate factors associated with OHRQoL. A total of 368 Malaysians were surveyed and examined for DMFT. Short-form oral health impact profile-Malaysia [S-OHIP(M)] and OIDP-M were used to measure OHRQoL. The OIDP-M was tested for reliability and validity. DMFT, S-OHIP(M), and OIDP-M between ethnicities were compared. Associations between ethnicity, DMFT, S-OHIP(M), and OIDP-M of Malays and Chinese were evaluated through partial correlation. Malays and Chinese had more filled teeth and DMFT compared with Indians. Malays reported worse OHRQoL through S-OHIP(M). Decayed teeth were positively associated with S-OHIP(M), physical, psychological, social disabilities, and handicap. For OIDP-M, decayed teeth were positively associated with OIDP-M, working, and sleeping. Missing teeth and ethnicity were positively associated with eating and speaking. Filled teeth were negatively associated with cleaning teeth. The OIDP-M was reliable and valid for evaluating OHRQoL. There were differences in DMFT and OHRQoL between ethnicities. Ethnicity affects OHRQoL, where Malays experienced worse OHRQoL due to dental problems.

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Demographic and socioeconomic inequalities in oral healthcare utilisation in Malaysia: evidence from a national survey

Cited by 19 publications

References 50 publications

Count data models for outpatient health services utilisation

Count data models for outpatient health services utilisation

Screening for type 2 diabetes and periodontitis patients (CODAPT-My©): a multidisciplinary care approach

Validation of the Malay Oral Impacts on Daily Performances and Evaluation of Oral Health-Related Quality of Life in a Multi-Ethnic Urban Malaysian Population: A Cross-Sectional Study

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