The COVID-19 pandemic and disruptions to maternal and child health services in public primary care Malaysia: a retrospective time-series analysis.

INTRODUCTION: The COVID-19 pandemic has posed significant challenges to healthcare systems worldwide. Maintaining essential health services, including maternal and child health (MCH), while addressing the pandemic is an enormous task. This study aimed to assess the impact of the COVID-19 pandemic on the utilisation of MCH services in Malaysian public primary care. METHODS: A retrospective analysis was conducted using national administrative data from 1124 public primary care clinics. Eight indicators were selected to measure service utilisation covering antenatal, postnatal, women's health, child health, and immunisation services. Interrupted time-series analysis was used to evaluate changes in levels and trends of indicators during four different periods: pre-pandemic (January 2019-February 2020), during pandemic and first lockdown (March-May 2020), after the first lockdown was lifted (June-December 2020) and after the second lockdown was implemented (January-June 2021). RESULTS: Most indicators showed no significant trend in monthly utilisation prior to the pandemic. The onset of the pandemic and first lockdown implementation were associated with significant decreasing trends in child health (-19.23%), women's health (-10.12%), antenatal care (-8.10%), contraception (-6.50%), postnatal care (-4.85%) and postnatal care 1-week (-3.52%) indicators. These indicators showed varying degrees of recovery after the first lockdown was lifted. The implementation of the second lockdown caused transient reduction ranging from -11.29% to -25.92% in women's health, contraception, child and two postnatal indicators, but no sustained reducing trend was seen afterwards. Two immunisation indicators appeared unaffected throughout the study period. CONCLUSION: The COVID-19 pandemic significantly impacted MCH services utilisation in Malaysia. While most MCH services were negatively affected by the lockdown implementation with varying degrees of recovery, infant immunisation showed resilience throughout. This highlights the need for a targeted preparedness plan to ensure the resilience of MCH services in future crises.

Spatial Accessibility of Primary Care in the Dual Public-Private Health System in Rural Areas, Malaysia.

Disparities in access to health services in rural areas represent a global health issue. Various external factors contribute to these disparities and each root requires specific remedial action to alleviate the issue. This study elucidates an approach to assessing the spatial accessibility of primary care, considering Malaysia's dual public-private system specifically in rural areas, and identifies its associated ecological factors. Spatial accessibility was calculated using the Enhance 2-Step Floating Catchment Area (E2SFCA) method, modified as per local context. Data were secondary sourced from Population and Housing Census data and administrative datasets pertaining to health facilities and road network. The spatial pattern of the E2SFCA scores were depicted using Hot spot Analysis. Hierarchical multiple linear regression and geographical weight regression were performed to identify factors that affect E2SFCA scores. Hot spot areas revolved near the urban agglomeration, largely contributed by the private sector. Distance to urban areas, road density, population density dependency ratios and ethnic composition were among the associated factors. Accurate conceptualization and comprehensive assessment of accessibility are crucial for evidence-based decision making by the policymakers and health authorities in identifying areas that need attention for a more specific and localized planning and development.

Count data models for outpatient health services utilisation.

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.

Matrix metalloproteinase-9 and tissue inhibitors of metalloproteinases 1 and 2 as potential biomarkers for gestational hypertension.

INTRODUCTION: Gestational hypertension (GH) is a common disorder during pregnancy that can progress to preeclampsia and cause various subsequent fatal complications. A cluster of enzymes, called matrix metalloproteinases (MMPs), and its specific inhibitors, tissue inhibitors of metalloproteinases (TIMPs), have been reported to be involved in the pathophysiology of GH. The purpose of this study was to examine circulating levels of MMP-9, TIMP-1 and TIMP-2 in pregnant women who had GH and those who were normotensive. METHODS: In a case-control study, the total levels of MMP-9, TIMP-1 and TIMP-2 in the sera of 108 pregnant patients were evaluated using enzyme-linked immunosorbent assays. 54 patients with GH (test group) and 64 normotensive pregnant women (control group) were included in the study. RESULTS: While MMP-9 levels showed a high level of expression in the GH group (p = 0.085), TIMP-1 and TIMP-2 levels showed low levels of expression for the same. Weak positive correlations were found on correlation analysis between maternal age and TIMP-1 in the GH group (r = 0.278, p < 0.05), and between gestational age and TIMP-2 in the control group (r = 0.318, p < 0.05). CONCLUSION: Our findings suggest that MMP-9 may be involved in the pathophysiology of GH. It may be of value to further evaluate MMP-9 as a potential biomarker for predicting preeclampsia in pregnant women.