Does context matter for the relationship between deprivation and all-cause mortality? The West vs. the rest of Scotland

Reproductive and child health transition among selected empowered action groups states of India: A district-level analysis

BACKGROUND

Health is an inseparable part of life and central to all life supporting systems. The reproductive and child health shares a major portion of public health cases that is crucial for socio-economic development. Studies on reproductive and child health have traditionally been focused on demographic aspects using socio-economic parameters. Given the emphasis of Sustainable Development Goal (SDG)-3 on health and well-being, it is imperative to understand the geo-spatial dimension with the visible transition of key health indicators of fertility, maternal and infant/child health in the high burdened districts within these high focus Empowered Action Group (EAG) states of Rajasthan, Madhya Pradesh, Uttar Pradesh and Bihar that make up nearly 40% of India's population with relatively laggard health status.

METHODOLOGY

This paper aims to understand the status and trend of key reproductive and child health indicators and vital statistics based on the recent representative demographic surveys. We intend to undertake a district level spatio-temporal analysis by developing District Composite Health Profile (DCHP) using Composite Index Method on selected 13 equally weighted key reproductive and child health indicators. The study has been carried out using data from National Family Health Survey-4 (2015-16) and National Family Health Survey-5 (2019-21) survey rounds. We employed geo-spatial techniques i.e. Moran's-I, and univariate LISA to comprehend the geographical clustering of high and low health burden districts and their heterogeneities at the district level.

RESULTS/CONCLUSIONS

The study highlights emerging inter-districts, and inter-state disparities over survey periods. With consistent improvement in the selected EAG states over time, the overall reproductive and child health status through DCHP along with each indicator was relatively better in the states of Rajasthan and worse in Bihar. Districts along the Terai belt in Uttar Pradesh and Bihar consistently performed sluggish during survey rounds. The geo-spatial clustering follows the political boundary of states, albeit with intra-state variations. Monitoring of key health indicators using composite index method provides a useful leverage for identifying priority districts/regions for universal health access that should also consider geographical space as an important policy dimension.

District level correlates of COVID-19 pandemic in India during March-October 2020

Background

COVID-19 is affecting the entire population of India. Understanding district level correlates of the COVID-19’s infection ratio (IR) is essential for formulating policies and interventions.

Objective

The present study aims to investigate the district level variation in COVID-19 during March-October 2020. The present study also examines the association between India’s socioeconomic and demographic characteristics and the COVID-19 infection ratio at the district level.

Data and methods

We used publicly available crowdsourced district-level data on COVID-19 from March 14, 2020, to October 31, 2020. We identified hotspot and cold spot districts for COVID-19 cases and infection ratio. We have also carried out two sets of regression analysis to highlight the district level demographic, socioeconomic, household infrastructure facilities, and health-related correlates of the COVID-19 infection ratio.

Results

The results showed on October 31, 2020, the IR in India was 42.85 per hundred thousand population, with the highest in Kerala (259.63) and the lowest in Bihar (6.58). About 80 percent infected cases and 61 percent deaths were observed in nine states (Delhi, Gujarat, West Bengal, Uttar Pradesh, Andhra Pradesh, Maharashtra, Karnataka, Tamil Nadu, and Telangana). Moran’s- I showed a positive yet poor spatial clustering in the COVID-19 IR over neighboring districts. Our regression analysis demonstrated that percent of 15–59 aged population, district population density, percent of the urban population, district-level testing ratio, and percent of stunted children were significantly and positively associated with the COVID-19 infection ratio. We also found that, with an increasing percentage of literacy, there is a lower infection ratio in Indian districts.

Conclusion

The COVID-19 infection ratio was found to be more rampant in districts with a higher working-age population, higher population density, a higher urban population, a higher testing ratio, and a higher level of stunted children. The study findings provide crucial information for policy discourse, emphasizing the vulnerability of the highly urbanized and densely populated areas.

Factors explaining regional variation in under-five mortality in India: An evidence from NFHS-4

Although child mortality has declined in India, pronounced regional and socioeconomic inequality exists. The study examines the effects of individual- and community-level characteristics on under-five mortality and investigates the extent to which they affect regional variation. The study is based on Indian National Family and Health Survey 4, 2015-16 data. A two-level logistic regression model was performed to examine the effects of the socio-economic characteristics, and multivariate decomposition analysis was done to assess the contribution of factors in the inter-regional under-five mortality differentials. Regional variation in the selected variables is observed. For instance, the percentage of children with small childbirth size varied from 9.7% in the southern to 21.6% in the northeastern region. The percentage of poor households, low educated mothers, and childbirths delivered at home facility were higher in the central and eastern region compared to the southern region. The multilevel analysis shows that the region of residence explained 15.8% variance, and community-level characteristics alone could explain 25.3% variation in the risk of under-five deaths. The decomposition analysis indicates that the average number of excess deaths in the central and eastern regions is higher compared to the other regions. The compositional differences account for 50.9% of the under-five mortality gaps between the south and north region, 80.9% of the gap between the south and east, and 42.9% of the gap between the south and central region of India. Special attention and targeted action are needed to address the underlying causes of low birth weight of children in all the regions of India. Region-specific interventions might be priorities; for example, north, and central regions, need an economic and educational uplift, while infrastructural and economic policies should be prioritized for the northeastern region. Also, region-specific community-level interventions are needed to improve child survival in India.

Neighbourhood socio-economic status and all-cause mortality in adults with atrial fibrillation: A cohort study of patients treated in primary care in Sweden

OBJECTIVE

Our aim was to study the potential impact of neighbourhood socio-economic status (SES) on all-cause mortality in patients with atrial fibrillation (AF) treated in primary care.

METHODS

Study population included adults (n=12,283) of 45 years and older diagnosed with AF in 75 primary care centres in Sweden. Association between neighbourhood SES and all-cause mortality was explored using Cox regression analysis, with hazard ratios (HRs) and 95% confidence intervals (95% CIs), and by Laplace regression where years to death (95% CI) of the first 10% of the participants were used as an outcome. All models were conducted in both men and women and adjusted for age, educational level, marital status, change of neighbourhood status, cardiovascular co-morbidities, anticoagulant treatment and statin treatment. High- and low-neighbourhood SES were compared with middle SES as reference group.

RESULTS

After adjustments for potential confounders, higher relative risk of all-cause mortality (HR 1.49, 95% CI 1.13-1.96) was observed in men living in low SES neighbourhoods compared to those from middle SES neighbourhoods. The results were confirmed using Laplace regression; the time until the first 10% of the men in low SES neighbourhoods died was 1.45 (95% CI 0.48-2.42) years shorter than for the men in middle SES neighbourhoods.

CONCLUSIONS

Increased rates of heart disease and subsequent mortality among adults in deprived neighbourhoods raise important clinical and public health concerns. These findings could serve as an aid to policy-makers when allocating resources in primary health care settings as well as to clinicians who encounter patients in deprived neighbourhoods.

A geospatial analysis of the relationship between neighbourhood socioeconomic status and adult severe injury in Greater Vancouver

Background

Every year, injuries cost the Canadian healthcare system billions of dollars and result in thousands of emergency room visits, hospitalisations and deaths. The purpose of this study was to explore the relationship between neighbourhood socioeconomic status (NSES) and the rates of all-cause, unintentional and intentional severe injury in Greater Vancouver adults. A second objective was to determine whether the identified associations were spatially consistent or non-stationary.

Methods

Severe injury cases occurring between 2001 and 2006 were identified using the British Columbia's Coroner's Service records and the British Columbia Trauma Registry, and mapped by census dissemination areas using a geographical information system. Descriptive statistics and exploratory spatial data analysis methods were used to gain a better understanding of the data sets and to explore the relationship between the rates of severe injury and two measures of NSES (social and material deprivation). Ordinary least squares and geographically weighted regression were used to model these relationships at the global and local levels.

Results

Inverse relationships were identified between both measures of NSES and the rates of severe injury with the strongest associations located in Greater Vancouver's most socioeconomically deprived neighbourhoods. Social deprivation was found to have a slightly stronger relationship with the rates of severe injury than material deprivation.

Conclusions

Results of this study suggest that policies and programmes aimed at reducing the burden of severe injury in Greater Vancouver should take into account social and material deprivation, and should target the most socioeconomically deprived neighbourhoods in Greater Vancouver.

Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Background

Spatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region.

Methods

In this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care.

Results

MOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected.

Conclusions

MOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.

Infant and child mortality in India in the last two decades: a geospatial analysis

Background

Studies examining the intricate interplay between poverty, female literacy, child malnutrition, and child mortality are rare in demographic literature. Given the recent focus on Millennium Development Goals 4 (child survival) and 5 (maternal health), we explored whether the geographic regions that were underprivileged in terms of wealth, female literacy, child nutrition, or safe delivery were also grappling with the elevated risk of child mortality; whether there were any spatial outliers; whether these relationships have undergone any significant change over historical time periods.

Methodology

The present paper attempted to investigate these critical questions using data from household surveys like NFHS 1992–1993, NFHS 1998–1999 and DLHS 2002–2004. For the first time, we employed geo-spatial techniques like Moran's-I, univariate LISA, bivariate LISA, spatial error regression, and spatiotemporal regression to address the research problem. For carrying out the geospatial analysis, we classified India into 76 natural regions based on the agro-climatic scheme proposed by Bhat and Zavier (1999) following the Census of India Study and all estimates were generated for each of the geographic regions.

Result/Conclusions

This study brings out the stark intra-state and inter-regional disparities in infant and under-five mortality in India over the past two decades. It further reveals, for the first time, that geographic regions that were underprivileged in child nutrition or wealth or female literacy were also likely to be disadvantaged in terms of infant and child survival irrespective of the state to which they belong. While the role of economic status in explaining child malnutrition and child survival has weakened, the effect of mother's education has actually become stronger over time.