The utility of geodemographic indicators in small area estimates of limiting long-term illness

Estimating BMI distributions by age and sex for local authorities in England: a small area estimation study

OBJECTIVES

Rates of overweight and obesity vary across England, but local rates have not been estimated for over 10 years. We aimed to produce new small area estimates of body mass index (BMI) by age and sex for each lower tier and unitary local authority in England, to provide up-to-date and more detailed estimates for the use of policy-makers and academics working in non-communicable disease risk and health inequalities.

DESIGN

We used generalised linear modelling to estimate the relationship between BMI with social/demographic markers in a cross-sectional survey, then used this model to impute a BMI for each adult in locally-representative populations. These groups were then disaggregated by 5-year age group, sex and local authority group.

SETTING

The Health Survey for England 2018 (cross-sectional BMI data for England) and Census microdata 2011 (locally representative).

PARTICIPANTS

A total of 6174 complete cases aged 16 and over were included.

OUTCOME MEASURES

Modelled group-level BMI as mean and SD of log-BMI. Extensive internal validation was performed, against the original data and external validation against the National Diet and Nutrition Survey and Active Lives Survey and previous small area estimates.

RESULTS

In 94% of age-sex are groups, mean BMI was in the overweight or obese ranges. Older and more deprived areas had the highest overweight and obesity rates, which were particularly in coastal areas, the West Midlands, Yorkshire and the Humber. Validation showed close concordance with previous estimates by local area and demographic groups.

CONCLUSION

This work updated previous estimates of the distribution of BMI in England and contributes considerable additional detail to our understanding of the local epidemiology of overweight and obesity. Raised BMI now affects the vast majority of demographic groups by age, sex and area in England, regardless of geography or deprivation.

Geodemographic insights on the COVID-19 pandemic in the State of Wisconsin and the role of risky facilities

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to impact the United States. While age and comorbid health conditions remain primary concerns in the community-based transmission of the virus, empirical evidence continues to suggest that substantial variability exists in the geographic and geodemographic distribution of COVID-19 infection rates. The purpose of this paper is to provide an alternative, spatiotemporal perspective on the pandemic using the state of Wisconsin as a case study. Specifically, in this paper, we explore the geographic nuances of COVID-19 and its spread in Wisconsin using a suite of spatial statistical approaches. We link detected hot spots of COVID-19 to local geodemographic profiles and the presence of high-risk facilities, including federal and state correctional facilities. The results suggest that the virus disproportionately impacts several communities and geodemographic groups and that proximity to risky facilities correlates to increased community infection rates.

Geodemographies of Breastfeeding Support

BACKGROUND

Mother-to-mother breastfeeding support organizations provide important information and guidance for helping mothers initiate and maintain breastfeeding, postpartum. However, the availability of this support is limited by a constellation of barriers, including race, culture, socioeconomic status, and geography.

RESEARCH AIMS

To identify the geodemographic composition of communities where breastfeeding support was available from the mother-to-mother support organizations Breastfeeding USA and La Leche League, identify underlying issues of equity, and highlight locations where more support resources may be needed.

METHODS

The locations of mother-to-mother support meetings were collected by ZIP code (N = 180) and were combined with a geodemographic database and exploratory spatial data analysis to explore the compositional characteristics of communities served (N = 1,173).

RESULTS

Significant gaps in the geographic distribution of breastfeeding support existed. While many metropolitan areas benefited from numerous mother-to-mother support groups and peer counselors, the geographic footprint of this support favored communities that were white, affluent, and suburban.

CONCLUSION

Spatial analytics combined with geodemographic analysis provide a unique perspective into the diverse landscape of mother-to-mother breastfeeding support groups at a local level. Our results highlighted inequities in the distribution of support provided and prescriptive guidance regarding where more resources may be needed.

Enabling and constraining successful reablement: Individual and neighbourhood factors

Using multilevel logistic regression to analyse management data of reablement episodes collected by Essex County Council, a UK local authority, this article identifies constraining and enabling factors for successful reablement. Overall, 59.5% of reablement clients were classed as able to care for themselves when assessed after 13 weeks following the reablement intervention (N = 8,118). Several age-related, disability, referral, and social factors were found to constrain reablement, but some of the largest constraining effects were neighbourhood deprivation as measured through the Index of Multiple Deprivation and, particularly, unfavourable geodemographic profiles as measured through Experian Mosaic consumer classifications. The results suggest that in order to optimise reablement, programmes should consider broader social and environmental influences on reablement rather than only individual and organisational aspects. Reablement might also be better tailored and intensified for client groups with particular underlying disabilities and for those displaying specific geodemographic characteristics.