Area-level socioeconomic characteristics, prevalence and trajectories of cardiometabolic risk

Associations between dimensions of the social environment and cardiometabolic risk factors: Systematic review and meta-analysis

Aim

The social environment (SE), including social contacts, norms and support, is an understudied element of the living environment which impacts health. We aim to comprehensively summarize the evidence on the association between the SE and risk factors of cardiometabolic disease (CMD).

Methods

We performed a systematic review and meta-analysis based on studies published in PubMed, Scopus and Web of Science Core Collection from inception to 16 February 2021. Studies that used a risk factor of CMD, e.g., HbA1c or blood pressure, as outcome and social environmental factors such as area-level deprivation or social network size as independent variables were included. Titles and abstracts were screened in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale. Data appraisal and extraction were based on the study protocol published in PROSPERO. Data were synthesized through vote counting and meta-analyses.

Results

From the 7521 records screened, 168 studies reported 1050 associations were included in this review. Four meta-analyses based on 24 associations suggested that an unfavorable social environment was associated with increased risk of cardiometabolic risk factors, with three of them being statistically significant. For example, individuals that experienced more economic and social disadvantage had a higher "CVD risk scores" (OR = 1.54, 95%CI: 1.35 to 1.84). Of the 458 associations included in the vote counting, 323 (71%) pointed towards unfavorable social environments being associated with higher CMD risk.

Conclusion

Higher economic and social disadvantage seem to contribute to unfavorable CMD risk factor profiles, while evidence for other dimensions of the social environment is limited.

Contributions of Multiple Built Environment Features to 10-Year Change in Body Mass Index and Waist Circumference in a South Australian Middle-Aged Cohort

Residential areas may shape health, yet few studies are longitudinal or concurrently test relationships between multiple residential features and health. This longitudinal study concurrently assessed the contributions of multiple environmental features to 10-year change in clinically measured body mass index (BMI) and waist circumference (WC). Longitudinal data for adults (18+ years of age, n = 2253) from the north-west of Adelaide, Australia were linked to built environment measures representing the physical activity and food environment (expressed for residence-based 1600 m road-network buffers) and area education. Associations were concurrently estimated using latent growth models. In models including all environmental exposure measures, area education was associated with change in BMI and WC (protective effects). Dwelling density was associated with worsening BMI and WC but also highly correlated with area education and moderately correlated with count of fast food outlets. Public open space (POS) area was associated with worsening WC. Intersection density, land use mix, greenness, and a retail food environment index were not associated with change in BMI or WC. This study found greater dwelling density and POS area exacerbated increases in BMI and WC. Greater area education was protective against worsening body size. Interventions should consider dwelling density and POS, and target areas with low SES.

Longitudinal associations of neighborhood socioeconomic status with cardiovascular risk factors: A 46-year follow-up study

OBJECTIVES

Neighborhood characteristics are increasingly recognized as important determinants of cardiovascular disease (CVD) risk. However, longitudinal studies on the health impacts of neighborhood characteristics are rare. We sought to investigate whether neighborhood socioeconomic status (NSES) during birth, childhood and adulthood is associated with CVD risk factors in adulthood.

METHODS

Using longitudinal data from the New England Family Study (n = 671) with 46-years of follow-up, participants' home addresses were geocoded at birth (mean age = 1.6 months), childhood (mean age = 7.1 years), and adulthood (mean age = 44.2 years) across Massachusetts and Rhode Island in the US from 1961 to 2007. We used multilevel models to evaluate associations of NSES across the life-course with systolic blood pressure, diastolic blood pressure and body mass index (BMI) in adulthood, adjusting for age, sex, race/ethnicity, mother's race, individual SES, and parental SES.

RESULTS

In fully adjusted models, one standard deviation higher NSES at birth was associated with a 1.9 mmHg lower SBP (95% CI: 3.8, -0.1) and 1.3 mmHg lower DBP (95%CI: 2.6,-0.03) in adulthood; while one standard deviation of higher NSES at adulthood was associated with 0.87 kg/m2 lower BMI (95%CI: 1.7, -0.1).

CONCLUSIONS

We found that living in a socioeconomically disadvantaged neighborhood early in life and in adulthood was associated with blood pressure and BMI, respectively, two established risk factors for CVD. Our findings support a longitudinal association between exposure to socioeconomically disadvantaged neighborhoods in early life and CVD risk factors in adulthood.

The relationship between living environment, well-being and lifestyle behaviours in young women in Shiraz, Iran

There has been increasing interest in understanding the influence of the living environment on individual and population health. While our understanding of the connection is growing, there has been limited published research focusing on socially and economically transitioning countries such as Iran or specific populations such as young women. This study explores the relationship between the physical and social living environment with well-being outcomes and lifestyle behaviours of young women in Shiraz, Iran, in 2013. Using a cluster convenience sampling technique, 391 young Iranian women with the mean age of 27.3 (SD: 4.8) participated in a cross-sectional survey (response rate 93%). A scale adapted from the British General Household Social Capital scale was used to assess living environment characteristics. The International Health and Behaviour survey, Satisfaction with Life Scale (SwL) and WHO Quality of Life questionnaire (WHOQOL-BREF) were used to measure lifestyle behaviours and well-being. The findings showed a moderate level of satisfaction with participants' living environment, with a mean score of 38.5 (SD: 7.7; score range: 11-45). There were correlations between physical and social neighbourhood environment, lifestyle behaviours and well-being outcomes (P < 0.05). Multiple regression analysis showed that the characteristics of living environments were determinants of quality of life (QoL), including physical, psychological, social and environmental QoL, as well as SwL (P < 0.05). Perceptions of individuals about their living environment issues were associated with demographic variables including ethnicity, income, level of education and occupation status. The current study shows how characteristics of the physical and social living environments play a significant role in shaping well-being and lifestyle behaviours among young Iranian women. Hence, there is a need for more focused attention to the meaning, measurement and building of neighbourhood livability, including both physical and social aspects of neighbourhood, in order to support QoL and SwL among young Iranian women, and enhance their healthy lifestyle behaviours.

Local modelling techniques for assessing micro-level impacts of risk factors in complex data: understanding health and socioeconomic inequalities in childhood educational attainments

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, "Micro-impact of Domain" and "Contribution of Domain", to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles.