19. Neighbourhoods and Population Health

Lecture 19: Neighbourhoods and Population Health

  • Professor Daniel Exeter, 2025

  • Focus: The impact of neighbourhoods on population health.

Lecture Objectives

  • By the end of this lecture, students should be able to:

    • Describe the characteristics of the built environment.

    • Describe the New Zealand Index of Multiple Deprivation (IMD) and explain how deprivation measures such as the IMD or NZDep differ from traditional measures of socioeconomic position (SEP).

    • Discuss how different aspects of the built environment can promote or restrict healthy behaviours.

    • Discuss features of urban planning that are health-promoting with respect to travel and encourage ‘healthy choices’.

Geographic Variations in Diagnosed Diabetes

  • Calculated Odds Ratios (OR) of the likelihood of adults aged 30+ years having diagnosed diabetes.

  • North Shore General Electoral District (GED) was used as the comparison group.

  • OROR for residents living in the Manurewa GED = 1.791.79 (1.691.69 to 1.911.91).

  • OROR was highest among residents living in the Mangere GED = 1.871.87 (1.761.76 to 2.002.00).

  • Source: Warin B, et al (forthcoming). Geography Matters: the prevalence of diabetes in the Auckland Region by age, gender and ethnicity. New Zealand Medical Journal.

Measuring Neighbourhood Deprivation

  • Deprivation is defined as “a state of observable and demonstrable disadvantage relative to the local community or the wider society or nation to which an individual, family or group belongs” (Townsend 1987).

  • It's a way of measuring people’s relative position in society.

  • Measures focus on material deprivation.

  • Tends to use a ‘deficit’ approach to describing population health, describing populations in relation to what they ‘don’t have’.

Variables Included in NZDep2018

  • Dimension of Deprivation & Description of Variable

    • Communication: People with no access to the Internet at home.

    • Income: People aged 18-64 receiving a means-tested benefit.

    • Income: People living in equivalised households with income below an income threshold.

    • Employment: People aged 18-64 unemployed.

    • Qualifications: People aged 18-64 without any qualifications.

    • Owned home: People not living in their own home.

    • Support: People aged <65 living in a single-parent family.

    • Living space: People living in equivalised households below a bedroom occupancy threshold.

    • Damp/Mould: People living in households that are always damp and/or always have mould greater than A4 size.

  • Source: Atkinson J, Salmond C, Crampton P (2020) NZDep2018 Index of Deprivation: Research Report. Department of Public Health, University of Otago, Wellington.

The NZ Index of Multiple Deprivation (IMD)

  • Measures the degree to which working-age people are excluded from employment.

  • Captures the extent of income deprivation by measuring state-funded financial assistance to those with insufficient income.

  • The Crime Domain measures the risk of personal and material victimizations (mostly theft, burglaries, and assaults): damage to person or property.

  • Proportion of people living in overcrowded housing and the proportion living in rented accommodation.

  • Identifies areas with a high level of ill health (hospitalizations, cancer) or mortality.

  • Captures youth disengagement, and the proportion of the working-age population without a formal qualification.

  • Measures the cost and inconvenience of traveling to access basic services (supermarkets, GPs, service stations, ECE, primary & intermediate schools).

IMD Domains and Weighting

  • Employment: # of working-age people receiving <$45 per day for job seeker support (28%).

  • Income: Amount of Working for Families Payment & Income Related Benefits (28%).

  • Crime: # of Victims of: Homicide + RO Physical/ Sexual Assault, Abduction and Kidnapping, Robbery, extortion + RO Trespassing + RO Theft + RO (5%).

  • Housing: # of people in rented housing, # of people in overcrowded housing, # of people in damp dwellings, # of people in housing without all the amenities on the census form (9%).

  • Health: SMR, # of emergency admissions, # of people with certain cancers, # of Hospitalizations related to selected Infectious diseases and Respiratory diseases (14%).

  • Education: # <17yo school leavers, # school leavers w/o NCEA L2, # working-age w/o qualifications, # youth not working or in education (14%).

  • Access: Distance to the nearest 3: GP/ A&M, Supermarket, Service Station, Primary + Intermediate Schools, ECE Centre (2%).

  • The IMD allows one to look at disadvantage in overall terms, as well as in terms of seven domains of deprivation.

  • The seven domains are weighted to reflect the relative importance of each domain in representing the key determinants of socio-economic deprivation, the adequacy of their indicators, and the robustness of the data that they use.

IMD18 Compared to NZDep18

  • We calculated the population-weighted average NZDep13 rank for each data zone.

  • We excluded 86 (1.4%) data zones with MBs without an NZDep13 score.

  • Spearman Correlation Coefficient: 0.92 (p <.0001).

Appropriate Uses of NZDep2018

  • Planning and resource allocation.

  • Research.

  • Advocacy.

  • Appropriate interpretation of NZDep2018: “People living in the most deprived neighbourhoods…” NOT “The most deprived people…”

The Ecological Fallacy

  • The error that arises when information about groups of people is used to make inferences about individuals.

Individual Income and Smoking Example

  • Income Levels:

    • Low income (less than $30,000).

    • Medium income ($30,000 to 70,000).

    • High income ($70,001 and above).

  • Example Data:

    • Low Income: Population 6, Smokers 5, % Smokers 83.

    • Medium Income: Population 5, Smokers 3, % Smokers 60.

    • High Income: Population 5, Smokers 2, % Smokers 40.

Neighbourhood Income and Smoking Levels

  • The neighbourhood values cannot be ascribed to the individual.

  • Orange neighbourhood might be described as the most deprived in this context, BUT individual incomes were: $12,000, $28,000, $32,000, $100,000.

  • Example Data:

    • Blue: Neighbourhood Mean Income $72,000, Smokers 1, % Smokers 25

    • Green: Neighbourhood Mean Income $70,500, Smokers 2, % Smokers 50

    • Yellow: Neighbourhood Mean Income $51,500, Smokers 3, % Smokers 75

    • Orange: Neighbourhood Mean Income $43,000, Smokers 4, % Smokers 100

Three Levels of Influence

  1. The Person

    • Age, sex, biology, behaviour risk factors, and lifestyle.

    • Attitudes to physical activity, health, and well-being.

  2. The Community

    • Availability of parks and recreation opportunities.

    • Family, friends, and neighbours’ habits in relation to healthy activities.

  3. The Environment

    • Physical, built, school, work, home.

    • Dahlgren, G & Whitehead M. (1991) "Policies and Strategies to Promote Social 9." Equity in Health. Stockholm: Institute for Future Studies.

Addressing Variations in Health

  • Upstream interventions tend to belong on the outermost arch on the Dahlgren and Whitehead model.

  • Interventions can target the individual, family and community, or the environment.

  • Examples:

    • Fluoridating water at source.

    • Taxation schemes.

    • ‘Green Prescriptions’.

What is a Healthy Environment?

  • The physical, social, or political setting(s) that prevent disease while enhancing human health and well-being.

  • Chronic diseases such as CVD and obesity are associated with environments that favor more sedentary lifestyles and/or poor nutrition.

  • See de Chalain & Stephenson (2009).

  • Elements of healthy environments include:

    • Clean air and water.

    • Appropriate housing.

    • Access to wholesome food.

    • Safe community spaces.

    • Access to transport.

    • Opportunities to incorporate exercise as part of daily life.

  • These are needed to maintain good health among the population.

The Built Environment

  • The built environment can be defined as: ‘all the buildings, spaces and products that are created, or at least significantly modified by people’.

  • It includes:

    • Structures: homes, schools, and workplaces.

    • Urban design: parks, business areas, and roads.

    • Above ground: electric transmission lines.

    • Below ground: waste disposal, subway trains.

    • Across land: motorways/ transportation network.

How Could the Built Environment Be Measured?

  • Measures are often context-specific depending on the research question/health outcome of interest.

  • Urban density: Population and/or employment density.

  • Land-use mix: Residential, commercial, industrial, wasteland.

  • Street connectivity: “Lollipop” neighborhoods vs. well-connected streets.

  • Community resources: Access to recreational facilities or healthy foods.

How Urban Design Can Improve Active Travel and Physical Activity

Concept

Key Features

Health-Related Benefit

Street connectivity

Grid-like pattern

Reduces distance between destinations, encouraging the use of ‘active transport’

Traffic calming

Street width, cycle lanes, traffic management, pedestrian crossings

Facilities that encourage walking and cycling and discourage driving

Mix of land uses

Different uses of land within a given zone

Increases opportunities for active transport

Public open spaces

Open spaces in close proximity to residents; pools, parks, playgrounds

Increase opportunities for physical activity

Air Pollution and Commuting Modes

  • Seven Modes Study: A 5 km journey along a popular commuting route – 7 modes, summer and winter data collection, carbon monoxide (Illustrative…)

  • Exposure the traffic pollution while commuting – Does mode matter?

  • PEYROUX, C., BUSSEN, L., COSTELLO, S.B., DIRKS, K. N. (2015) Weather & Climate, 35, 2-12.

  • Considerations:

    • Average air pollution exposure.

    • Breathing rate and travel time.

    • Distance from the road centerline.

Built Environment and Health Outcomes

  • The lecture explores whether individuals are overweight due to sedentary personal habits or due to badly-planned built environments.

  • Built environment, PA, and obesity: 5km ‘buffer’ around survey respondents, depicting access to recreational facilities (Gordon-Larsen, P. et al. Pediatrics 2006;117:417-424).

  • Fitness centers, overweight & physical activity (Gordon-Larsen, P. et al. Pediatrics 2006;117:417-424 (Table 4)).

  • As the Number of Recreational Facilities increases:

    • Overweight Adjusted OR (95% CI) decreases.

    • ≥5 Bouts MVPA Adjusted OR (95% CI) increases.

    Conventional vs. What Your Doctor Didn't Tell You

  • The lecture concludes by contrasting conventional health advice with the realities of how social and economic factors influence health outcomes.

  • Highlights the importance of addressing systemic issues rather than solely focusing on individual behaviors.