TABLE 1.
Summary of study characteristics
| Author | Year | Country of study | Setting/ design | Rurality description | Sample size | Participant details | Mean age (SD) | Sex | Mental health measures | Environmental measures |
|---|---|---|---|---|---|---|---|---|---|---|
| Studies of green space | ||||||||||
| Akpinar, Barbosa‐Leiker 38 | 2016 | USA | Explore specific types of green spaces associated with mental and general health using data from Behavioral Risk Factor Surveillance System Survey and National Land Cover Data | State with a variety of eco‐zones (heavily forested, shrubland, grassland and both irrigated and dryland agriculture) | N = 5148 | Residents of Washington State | 52.40 | Male 39.2%; Female 60.8% | Mental health complaints (last 30 d); anxiety‐depression complaints (last 14 d) | Percentage of green space type by ZIP code |
| Alcock, White 41 | 2015 | England | Examine relationships between types of green space and mental health using data from 18‐y longitudinal British Household Panel Survey linked with Land Cover Map (LCM) | Rural residential areas | N = 2020 (12 697obs) | Residents in English rural neighbourhoods | 47.59 | Female 52.4% | GHQ‐12; 2‐item second standard scoring method | 10 aggregate land cover classes in the LCM2007 |
| Losert, Schmauss 39 | 2012 | Germany | Test environmental risk factors for mental illness in rural catchment area | Rural municipalities | N = 4198 | Psychiatric patients living in study region | NA | NA | Hospital admission data for schizophrenia and affective disorders from 2006 to 2009 | Data on proportion of forest and agricultural areas |
| Nishigaki, Hanazato 40 | 2020 | Japan | Examine relationship between green space and depression among older adults living in rural (and urban) areas | Rural municipalities, nationwide | N = 33 823 | Older adults (age 65+) living in the community | NA | NA for rural sample (full sample: female 51.5%) | Geriatric Depression Scale (GDS) | Total green space, grass, tree and field ratios (tertiles) from satellite imagery, at the school district level |
| Studies of drought | ||||||||||
| Austin, Handley 28 | 2018 | Australia | Examine drought‐related stress using data from longitudinal cohort study—Australian Rural Mental Health Study (ARMHS) | Non‐metropolitan New South Wales | N = 664 | Living or working on a farm | 55‐64 27.7% | Male 43.7%; Female 56.3% | K10; personal and community drought‐related stress | Drought conditions by comparing rainfall during prior 12 mo |
| Brew, Inder 26 | 2016 | Australia | Determine whether farming is associated with poorer health using data from ARMHS study | Non‐metropolitan New South Wales | N = 1284 | Farmers and non‐farming workers (other rural workers and farm residents employed elsewhere) | 48.3 (11.9) | Female 57% | K10; PHQ‐9; item on self‐report overall mental health | Remoteness of location of residence (ARIA+); item on drought stress |
| Edwards, Gray 21 | 2015 | Australia | Impact of drought on mental health using data from stratified random Rural and Regional Family Survey | Rural and regional ‐ agricultural | N = 8000 | Adults living in agricultural areas | 46.5 (10.91) | Female 54.2% | 5‐item Mental Health Inventory Form SF‐36 | Area‐based self‐report drought measure |
| Friel, Berry 45 | 2014 | Australia | Association between drought exposure, food insecurity and mental health using data from longitudinal study Household, Income and Labour Dynamics in Australia (HILDA) Survey | Rural and urban | N = 5012 | Wave 7 survey participants aged 15+ | NA | NA | K10 | Monthly rainfall data from Australian Bureau of Meteorology |
| Guiney 29 | 2012 | Australia | Examination of farming suicides during prolonged drought based on reports to State Coroner | NA | N = 110 | Farmers and primary producers in Victoria | 40‐49 22% | Male nearly 95% | Intentional self‐harm fatalities data obtained from National Coroners Information System for 7‐y period | NA |
| Gunn, Kettler 22 | 2012 | Australia | Examination of psychological distress and coping in drought‐affected area | Rural farming | N = 309 | Farmers or spouses of farmers in South Australia | 51.81 (11.69) | Male 63.4%; Female 34.6% | K10 | NA |
| Hanigan, Butler 30 | 2012 | Australia | Investigation of suicide in rural populations with a previously established climatic drought index | Rural and urban regions of New South Wales (NSW) | NA | Residents of 11 regions in NSW | NA | NA | Data on suicides 1970‐2007 | Hutchinson Drought Index |
| Hanigan, Schirmer 23 | 2018 | Australia | Association between drought and distress using survey questionnaire | Rural area | N = 5312 | Residents of Victoria—farmers and non‐farmers | NA | Male 41.5%; female 57.7% | K10 | Hutchinson Drought Severity Index |
| Kelly, Lewin 27 | 2011 | Australia | Individual and contextual factors influencing mental health within rural communities using data baseline sample from ARMHS | Non‐metropolitan regions of New South Wales | N = 2462 | Residents aged 18‐65 | 55.6 (14.5) | Female 59% | K10 | Data on drought severity and remoteness (ARIA+and ASGC) |
| Mann, Freyens 43 | 2016 | Australia | Impact of natural and economic crises on structural change in farming sector using data from Australian Regional Well‐being Survey | Rural and regional | N = 2492 | Dryland farmers and irrigators | NA | NA | 1 item on happiness (in the last 4 weeks) | 1 item each on drought and other natural disaster (over the last 5 y) |
| O'Brien, Berry 24 | 2014 | Australia | Quantitatively identify association between patterns of drought and mental health using HILDA Survey and rainfall data from Australian Bureau of Meteorology | Rural and urban | N = 5012 | People aged 15+ | 40‐55—rural 33.04 (0.02), urban 31.38 (0.01) | Male—rural 51.62 (0.01), urban 47.28 (0.01) | K10 | Drought patterns for 2001‐2008 |
| Parida, Dash 31 | 2018 | India | Examine the effects of drought and flood on farmer suicides using state‐level panel data for 1995‐2011 | Agricultural | NA | Residents of 17 Indian states | NA | NA | Suicide data from annual report from National Crime Record Bureau | Flood data from Dartmouth Flood Observatory; Drought data from Department of Land Resources |
| Stain, Kelly 44 | 2011 | Australia | Examine factors associated with drought impact | Rural and remote | N = 302 | Randomly selected residents of NSW aged 18+ | 53 | Female 57% | K10; Worry about Drought Scale | Drought status |
| Wheeler, Zuo 25 | 2018 | Australia | Large‐scale assessment of Murray‐Darling Basin irrigators’ mental health | Irrigation districts | N = 1000 | irrigators | NA | NA | K10 | Items on drought, water availability |
| Studies of land degradation | ||||||||||
| Canu, Jameson 36 | 2017 | USA | Examine relative risk for mental health diagnoses in areas with mountaintop removal (MTR) using data from State Emergency Department Database | Residential area | N = 1 380 394 | Kentucky State ED outpatients in a calendar year aged 18+ | 42.2 (18.19) | Female 58.1% | Rates of emergency department diagnosis for depressive disorders, substance use disorders and anxiety disorders in 2008 | ZIP code to determine active MTR area and rural status |
| Kallioniemi, Simola 46 | 2016 | Finland | Stress among Finnish dairy farmers using cross‐sectional survey | Dairy farms | N = 265 | Finnish dairy farmers | 47.8 (10.35) | Men 56%; female 44% | MBI‐GS | Items on work and living environment resources |
| Morgan, Hine 47 | 2016 | Australia | Examine contribution of coal seam gas (CSG) extraction to global stress burden and mental health of farmers | NA | N = 378 | Farmers or their partners | 53.08 (10.28) | Male 50.5%; female 49%; other 0.5% | DASS‐21 | Items on farm stress, that is weather, CSG concerns; engagement with CSG industry |
| Speldewinde, Cook 37 | 2009 | Australia | Examine the effects of environmental degradation (dryland salinity) on mental health | Dryland agricultural areas | N = 2669 | Residents of southwest Western Australia | 20‐39 42% | Male 38%; Female 62% | Hospital cases (1st admission) for depression | Soil and landscape mapping as a measure of dryland salinity |
| Studies of climate conditions and extreme weather | ||||||||||
| Daghagh Yazd, Wheeler 32 | 2020 | Australia | Longitudinal examination of whether area‐level climatic conditions and water scarcity were associated with poorer mental health for farmers | Rural areas | N = 235 | Active farmers living in the Murray–Darling Basin region of Australia | 49.7 (16.2) | Female 35%; Male 65% | MHI‐5 subscale | Water scarcity (measured through decreased rainy days; drought period; increased summer temperatures; reduced water allocations; lower soil moisture) |
| Howard, Ahmed 33 | 2020 | USA | Impact of perception of climate change on mental health among rural agricultural populations using cross‐sectional survey | Rural agricultural | N = 125 | Farmers and ranchers aged 18+ from Montana | 35‐54 49.2% | Mostly male | Modified GAD‐7; PHQ‐9 | 3 items from Climate Change in the American Mind; 4 items from Climate Harm Scale |
| Pailler and Tsaneva 34 | 2018 | India | Test effects of extreme weather and precipitation on psychological well‐being using data from World Health Survey (WHS) and Study on Global AGEing and Adult Health (SAGE) | Rural and urban | N = 16 227 | Adults aged 18‐60 | NA | Female—WHS 52%, SAGE 68% | Items on depression symptoms | Climate data using GPS coordinates—average monthly temperature and total monthly precipitation |
| Wind, Joshi 35 | 2013 | India | Examine immediate impact of recurrent flood on mental health | Rural district | N = 615 | Affected population in Bahraich, Uttar Pradesh, compared with non‐affected group in the same region | Affected 46.03 (15.74); non‐affected 47.23 (13.92) | Affected—male 61%, female 39%; non‐affected male 54.9%, female 44.1% | HSCL‐25; SF‐12 | NA |
| Studies of engagement in natural resource management activities | ||||||||||
| Hounsome, Edwards 42 | 2006 | Wales | Exploration of farmer health as a variable in adoption of agri‐environment schemes | Farm households | N = 111 | Farmers | NA | NA | SF‐36 | Involvement in agri‐environment schemes |
| Moore, Kesten 5 | 2018 | Australia | Explore benefits gained by involvement in management of land for conservation using mixed methods | Rural regions in Victoria | N = 102 | Members of community‐based land management group and controls matched by age and sex | 45‐64 nearly 50% | Male 63%; female 37% | 1 item feel anxious; 1 item feel depressed | NA |
Abbreviations: ARMHS, Australian Rural Mental Health Study; DASS‐21, 21‐item Depression Anxiety and Stress Scale; ED, emergency department; GAD‐7, 7‐item Generalized Anxiety Disorder; GDS, Geriatric Depression Scale; GHQ‐12, 12‐item General Health Questionnaire; HILDA, Household; HSCL‐25, 25‐item Hopkins Symptom Checklist; Income and Labour Dynamics in Australia; K10, Kessler‐10 Distress Scale; MBI‐GS, Maslach Burnout Inventory—General Survey; MHI‐5, 5‐item Mental Health Inventory; NA, not applicable; PHQ‐9, 9‐item Patient Health Questionnaire; SF‐12, 12‐item Short‐Form Health Survey; SF‐36, 36‐item Short‐Form Health Survey.