http://orcid.org/0000-0003-3327-5580
Figures
Abstract
Background
Free provision of tangible goods that may improve health is one approach to addressing discrepancies in health outcomes related to income, yet it is unclear whether providing goods for free improves health. We systematically reviewed the literature that reported the association between the free provision of tangible goods and health outcomes.
Methods
A search was performed for relevant literature in all languages from 1995-May 2017. Eligible studies were observational and experimental which had at least one tangible item provided for free and had at least one quantitative measure of health. Studies were excluded if the intervention was primarily a service and the free good was relatively unimportant; if the good was a medication; or if the data in a study was duplicated in another study. Covidence screening software was used to manage articles for two levels of screening. Data was extracted using an adaption of the Cochrane data collection template. Health outcomes, those that affect the quality or duration of life, are the outcomes of interest. The study was registered with PROSPERO (CRD42017069463).
Findings
The initial search identified 3370 articles and 59 were included in the final set with a range of 20 to 252 246 participants. The risk of bias assessment revealed that overall, the studies were of medium to high quality. Among the studies included in this review, 80 health outcomes were statistically significant favouring the intervention, 19 health outcomes were statistically significant favouring the control, 141 health outcomes were not significant and significance was unknown for 28 health outcomes.
Citation: Persaud N, Steiner L, Woods H, Aratangy T, Wanigaratne S, Polsky J, et al. (2019) Health outcomes related to the provision of free, tangible goods: A systematic review. PLoS ONE 14(3): e0213845. https://doi.org/10.1371/journal.pone.0213845
Editor: Ester Villalonga-Olives, Institute of Medical Psychology and Medical Sociology, GERMANY
Received: September 4, 2018; Accepted: March 3, 2019; Published: March 20, 2019
Copyright: © 2019 Persaud et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: AP and NP are supported as Clinician Scientists by the Department of Family and Community Medicine, Faculty of Medicine, University of Toronto. AP is also supported by a fellowship from the Physicians’ Services Incorporated Foundation. NP is also supported by the Canada Research Chairs program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Disparities in health along socioeconomic lines are well established: groups with lower income and socioeconomic position consistently experience worse health outcomes, including higher rates of mortality.[1, 2] One of many possible explanations for better health outcomes among those with higher socioeconomic status is that income allows greater access to tangible goods that can improve health, such as safe shelter, healthy foods, clean water, and essential medicines. Worse health outcomes among lower socioeconomic status groups may be explained by reduced access to education and child care, exposure to hazards such as air pollution or contaminated drinking water, exposure to violence, reduced access to health care services, or discrimination based on gender, ethnicity or other characteristics.[3, 4] Some of these potential alternative explanations may be indirectly related to access to tangible goods, such as water filtrations systems that can mitigate effects of contaminated water and medicines that may mitigate the effects of poor access to health care services. The importance of tangible goods has long been recognized through accounting for “non-cash” income, such as the value of housing provided by governments, and by defining poverty based on the cost of tangible goods (as in reference budgets that are baskets of goods and services that are considered necessary to reach an acceptable standard of living for an individual household within a given country, region or city) and essential services rather than based on relative income level.[5, 6]
If people lack a good that is required for their health and well-being, a simple response is to provide it for free. This approach appears to underpin many governmental and non-governmental programs routinely devote substantial resources to distributing goods to people in need.[7–9] Yet it is unclear whether providing goods for free promotes health. Free tangible goods may not be used as intended or at all: their positive health effects may not overcome other causes of poor health, or they may even cause unintended harm (e.g. providing safety equipment such as bicycle helmets could encourage risky behavior).[10] Providing people with free goods could complement other efforts to promote health, such as providing services like healthcare,[11] and providing a Basic Income.[12, 13] The receipt of free tangible goods could free up limited household income or resources that would otherwise be consumed in obtaining those goods and this additional disposable income may result in improved health.
We are not aware of any previous systematic effort in the existing scientific literature to assess whether providing free goods promotes health. We systematically reviewed the literature for studies that reported the association between the free provision of tangible goods and health outcomes.
Methods
Search strategy
A search strategy was developed in consultation with an information specialist. This systematic review was registered on PROSPERO (CRD42017069463, Aug 30 2017).
We defined “tangible goods” as a physical good or object that could be given to persons or families. We generated a list of items which were hypothesized to be distributed without charge to patients or study participants. The list of items was sent to several other researchers for feedback who had expertise in primary health care, social determinants of health, health economics, epidemiology, public health, homelessness, housing, refugee health, access to healthy food and income security. After feedback was received, a final list of key terms was created with all suggestions included (S1 File, Search strategy).
Key terms were searched in the following databases: EMBASE, MEDLINE, CINAHL, PsycINFO, Cochrane, ProQuest databases (others could include Applied Social Sciences Index and Abstracts (ASSIA), FRANCIS, International Bibliography of the Social Sciences (IBSS), PAIS International, ProQuest Family Health, ProQuest, Social Services Abstracts, Sociological Abstracts) in all languages from 1995-present. We also looked through trial registries. The search was conducted in June 2017.
Inclusion criteria
Eligible studies were observational (e.g. case-control, cohort, before-after, pre-post or longitudinal), and experimental studies (e.g. randomized controlled trial), which had at least one tangible item provided free of cost to participants. Examples of free goods included transit passes, food boxes, infant goods, bicycle helmets, condoms, needles, and other drug paraphernalia. Studies had to have at least one quantitative measure of health. We understood “health” as the quality or duration of life. Although housing retention is not a health outcome, it was treated as such because housing is closely related to quality of life.[14]Included studies were also required to have a comparison or control group that allowed the effect of the free good to be measured. Studies published between January 1995 and May 2017 were eligible.
Exclusion criteria
We excluded studies in which a service such as advice, health screening procedure or a diagnostic test was provided; if the intervention was primarily a service and the free good was relatively unimportant (e.g. giving participants a voucher for a health service); if the good was a medication (e.g. nicotine replacement, contraception, naloxone kits); or if the data in a study was duplicated in another study (duplicated data was defined as data from the same participant at the same timepoint).
Screening
Covidence screening software [15] was used to manage articles while screening. In level one screening, all titles and abstracts were reviewed to determine if they met the inclusion criteria for the study. Level two consisted of screening the full text of articles to determine whether they met the inclusion criteria. Each article was appraised by two reviewers (LS and HW) for both levels and disagreements were discussed. If the reviewers did not come to a decision, a third investigator (NP) was consulted.
We attempted to include only one report of each health outcome. We excluded reports where both the outcomes and participants were the same as a study that was already included. We included reports where the participants and outcomes only partially overlapped between reports. If multiple reports included the same outcome for the same participants, we included that outcome only once.
Extraction technique
Publication information, study characteristics, participant demographics, the health outcomes measured in the study and the quantitative results were extracted from each study by one reviewer using an adaption of the Cochrane data collection template. [16]
Quality appraisal
The quality of each article was appraised by two individual reviewers using the Cochrane Risk of Bias assessment tool for randomized control trials [17] and ROBINS 1 assessment tool for non-randomized control trials. [18] The Cochrane Risk of Bias tool assesses seven potential sources of bias including random sequence generation, allocation concealment, blinding of participants, blinding of outcome assessments, incomplete outcome data, selective reporting, and funding source. [17] The ROBINS 1 tool also assesses seven potential sources of bias including bias due to confounding, bias in selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions, bias due to missing data, bias in measurement of outcomes, and bias in selection of the reported results. [18] We did not exclude any studies based on the risk of bias assessment.
Results
Literature search
The initial search identified 3370 articles of interest. In the first level of screening based on abstract review, 3132 articles were excluded, leaving 238 articles for full manuscript review. This second level of screening removed a further 179 articles yielding a final set of 59 articles which met full eligibility criteria (Fig 1).
Study characteristics
The 59 included studies included a range of 20 to 252 246 participants with a median of 872·5. The length of the studies ranged from two to 180 months with a median of 15·5 months. Of the 59 articles, 29 were randomized controlled trials (RCTs) and 30 were observational studies.
Among the 59 included studies, 45 (76·3%) were from countries that are considered high income according to the 2016 World Bank Report.[20] These countries included the USA (20 studies), Canada (13 studies), United Kingdom (four studies), Norway (two studies), Israel (two studies), Ireland (one study), New Zealand (one study), Australia (one study), and France (one study).Fourteen studies (23·7%) were from countries considered low or medium income by the 2016 World Bank Report.[20] These countries included India (three studies), Cameroon (two studies), and one study each from Mexico, Colombia, Ukraine, Pakistan, Ghana, Kenya, Nigeria, China and Zanzibar.
Among the 59 included studies, the free goods provided were housing (20 studies), food (17 studies), safety equipment (six studies), insecticide treated nets (five studies), hygiene, and water sanitation (six studies) and miscellaneous (five studies).
Risk of bias
Among the RCTs there were: no studies judged to be at a low risk of bias in all domains, one (3·4%) study was at a low or unknown risk of bias for all domains and 28 (96·6%) studies were at a high risk of bias in at least one domain (Fig 2). Among observational studies, there was: one (3·3%) study judged to be at a low risk of bias or no information in all domains, 11 (36·7%) studies at a low or moderate risk of bias or no information for all domains, 13 (43·3%) studies at serious risk of bias in at least one domain (but not at critical risk of bias in any domain), and five (16·7%) studies at critical risk of bias in at least one domain (Fig 3). Risk of bias assessment data is available as S1 Table, Cochrane risk of bias assessment for RCTs and S2 Table, ROBINS 1 risk of bias assessment for observational studies.
Results by type of good
Housing.
There were 24 940 participants in the 20 housing studies (there was some overlap in participants between studies; see the Methods section) (Table 1). All studies were conducted in either Canada (12 studies) or the USA (eight studies). Nineteen of these studies (95%) had a co-intervention, of which eighteen were “Housing First” programs. For example, in addition to housing, the intervention offered participants treatment for various addictions, mental health challenges and other social supports. [21] The primary reported outcomes in housing studies were stable housing (11 studies, 55%);substance use (10 studies, 50%); psychiatric symptoms or mental health,(eight studies, 40%); quality of life, including QoLI-20, community functioning (MCAS)and community integration (CIS-PHYS and CIS-PSYCH)(eight studies, 40%); health status, including BMI, waist circumference, physical health ailments and health assessments using EQ5D-VAS, and physical SF-12 assessment forms (six studies, 30%); food security (two studies, 10%); and death (one study, 5%). The study durations ranged from six months to 180 months. Housing studies reported a total of 114 outcomes (with duplicates removed), of which 42 were statistically significant, 62 were not significant, and significance was unknown for 10 outcomes. Of the 42statistically significant outcomes, 37 outcomes (from 15 different studies) favoured the intervention, and five outcomes (from two different studies) favoured the control.
Food.
There were 307 583 participants in the 17 food studies (Table 2). Food studies were conducted in USA (11 studies), Norway (two studies), Mexico (one study), Colombia (one study), New Zealand (one study), Ukraine (one study). One study (5·9%)involved a co-intervention consisting of nutrition and education counselling. [41] The most commonly measured health outcome was Body Mass Index (BMI) measured in 12studies (70·6%). The study durations ranged from four to 96 months. Food studies reported a total of 73 outcomes, of which 28 were statistically significant, 41 were not significant, and significance was unknown for four outcomes. Of the 28 statistically significant outcomes, 22 outcomes (from eight different studies) favoured the intervention, and six outcomes (from three different studies) favoured the control group.
Hygiene/Water sanitation.
There were 10 504 participants in the six hygiene or water sanitation studies (the household was the unit of analysis in two studies) (Table 3). The free goods distributed were toothbrushes and toothpaste (two studies), a drinking water disinfectant (two studies), and free soap (two studies). The studies were conducted in India (three studies), England (one study), Pakistan (one study), and Israel (one study). Three studies (50%) involved a co-intervention which consisted of social marketing, and educational campaigns. [58–60] The most common outcomes were diarrhoea prevalence in three studies (50%); infection prevalence in two studies (33·3%); and prevalence of dental carries reported in two studies (33·3%). The study durations ranged from nine months to 60 months. These studies reported a total of 34 outcomes, of which 15 were statistically significant, 11 were not significant, and significance was unknown for eight outcomes. All of the 15statistically significant outcomes (from three different studies) favoured the intervention.
Insecticide treated nets (ITN).
There were 7661 participants in five studies providing ITN (Table 4). The studies were conducted in Cameroon (two studies), Ghana (one study), Kenya (one study), and Nigeria (one study). Three studies (60%) involved a co-intervention consisting of additional medical care, a social marketing campaign and preventative sulfadoxine-pyrimethamine treatment. [64–66] The most common outcomes measured were parasitaemia in three studies (60%); anemia in two studies (33·3%); malaria in two studies (33·3%). Other outcomes included mortality and birth weight. The study durations ranged from four months to 36 months. Eleven outcomes were reported, of which three were statistically significant, and eight were not. Of the three statistically significant outcomes (from three different studies), all favoured the intervention.
Safety equipment.
Six studies provided free safety equipment including smoke alarms, hip protectors, mouth guards, and safety equipment for young children (e.g. stair gates and cupboard locks) (Table 5). We were unable to identify the total number of participants in these studies because some reports did not specify this information. The studies were conducted in England (two studies), USA (one study), Ireland (one study), Israel (one study) and Australia (one study). Five studies (83·3%) involved a co-intervention consisting of educational materials and sessions,[10, 69–71] as well as advice,[72] and one study offered stickers to promote the use of safety equipment.[71] The common outcome reported in all six studies was injury. Study duration ranged from six months to 72 months. Safety equipment studies reported a total of 23 outcomes, of which eight were statistically significant, 11 were not significant, and significance was unknown for four outcomes. Of the eight statistically significant outcomes, all eight outcomes (from three different studies) favoured the control and, according to the explanations provided in the articles, this may be been due to infrequent use of the safety equipment.[10, 71, 73]
Miscellaneous.
Five studies involved a miscellaneous set of outcomes (Table 6). The distributed free goods included glucometer test strips for diabetic patients, glucometers, sunscreen, bus passes, and a mobile phone. Three studies (60%) involved a co-intervention consisting of a glucometer (intervention was test strips),[74] educational material and counselling (for the glucometer study) [75] as well as an automated message and calling card to reach participants’ primary care physicians (for the mobile phone study) [76]. The outcomes measured included HbA1c, blood glucose, triglycerides, Low Density Lipoprotein (LDL-C), Body Mass Index (BMI), waist circumference, rate of sunburns, and mortality rate. The study durations ranged from two months to 12 months. These studies reported 13 outcomes, of which three were statistically significant, eight were not significant, and significance was unknown for two outcomes. All three statistically significant outcomes (from two different studies) favoured the intervention.
Results by health outcome
In addition to analyzing the results of studies categorized by type of free good distributed to participants, we combined results from the reviewed studies for the health outcomes of mortality and diarrhea because these two outcomes were reported in studies of different categories of goods.
Mortality.
Mortality was reported as a health outcome in three studies of mosquito nets (one study), housing vouchers (one study), and mobile phones (one study) including 17 730 participants. The first study gave families with children under five an insecticide treated insect net in Kenya. The study found that receiving a mosquito net was a significant predictor of reduced mortality (rate ratio: 0·56; 95% confidence interval (CI): 0·33–0·96).[65] The second study gave a housing voucher to families of children living in public housing in the USA.[24] Receiving a housing voucher was not a significant predictor of mortality in any of the 3 categories; deaths from disease (p = 0·84), deaths by homicide (p = 0.81),and accidental deaths (p = 0·19).[24]The final study gave phones to pregnant women in Zanzibar. [76] Mortality was recorded in three ways: stillbirth (unadjusted odds ratio (UOR): 0·62; 95%CI: 0·31–1·22), perinatal mortality (UOR: 0·49; 95%CI: 0·27–0·90), and neonatal mortality (UOR: 0·85; 95%CI: 0·37–1·95). Receiving a free phone significantly reduced perinatal mortality. [76]
Diarrhea.
Diarrhea was reported as a health outcome in four studies of food (one study), and hygiene and water sanitation (three studies), which included 8382 participants. The first study conducted in Pakistan included households in squatter settlements receiving either bleach, hand washing supplies, flocculant-disinfectant, or flocculant- disinfectant plus hand washing. [61] The authors concluded that receiving any of the free goods, as well as the intense community-based intervention, which included meetings and presentations to community leaders and residents about the importance of hygiene wand water contamination, reduced the daily longitudinal prevalence of diarrhoea; however, the level of statistical significance was not reported. [61]The second study, conducted in Colombia, gave primary school children a school snack. [47] The authors found that the rate of days per child year of diarrhoea (unadjusted rate ratio (URR):0·68; CI: 0·63–0·73), and diarrhoea with vomiting (URR: 0·63; CI: 0·52–0·75) were significantly reduced with the provision of a school snack.[47] The third study, conducted in India, gave children under the age of five sodium dichloroisocyanurate tablets.[59] The authors found that the longitudinal prevalence of diarrhoea for children given sodium dichloroisocyanurate tablets was not significantly different from the control (prevalence ratio: 0·95; CI: 0·79–1·13). [59]The final study, conducted in India, distributed soap to households with children under five, and outcomes were assessed for the target children, as well as their family, including siblings.[60] The authors reported significant relative risk reductions (RRR) in diarrhoea prevalence related to the provision of free soap among four groups: target children (RRR: 25·3%; CI 36·6–2·3); children aged five and under (non-target) (RRR: 32·5%; CI 41·1–3·8); children aged six-15 (non-target) (RRR: 30%; CI 38·7–6·6); and whole families (observed RRR 30·7%: CI 37·5–5·5). [60] As such, three of the four studies reported that diarrhoea was significantly reduced with the provision of free goods.
Interpretation
The results of this systematic review provide evidence that free goods can improve health outcomes in certain circumstances, although there are also important gaps and limitations in the existing literature. Housing provision for people with serious mental health conditions in high-income countries and food provision to low-income children in high-income countries are supported by the largest number of studies. Of the 59 reviewed studies involving 379 932 participants (most were individuals but some were households) that examined the health effects of free goods, the most commonly studied free goods were housing (20 studies) and food (17 studies). Among the 268 total outcomes reported, the most commonly reported outcomes were housing retention in 12 housing studies and BMI in 12 food studies. Four RCTs were deemed to be unclear or at high risk of bias, and one non-RCT was rated as serious, critical or no information, in all risk of bias categories. Therefore, overall the studies were of medium to high quality in terms of bias. Among the studies included in this review, 80 health outcomes were statistically significant favouring the intervention, 19 health outcomes were statistically significant favouring the control, 141 health outcomes were not significant, and significance was unknown for 28 health outcomes.
The rationale underpinning how the provision of free tangible goods impacts health was typically not stated in the reviewed studies. However, we identify four related concepts that help us understand the rationale for providing free tangible goods. First, facilitating access to a good that is capable of promoting health should promote health unless there are unintended negative effects or implementation problems. We did in fact find some studies where those receiving a free good had worse health outcomes (e.g. hip protectors were associated with an increased risk of hip fractures).[71] Second, if poverty is defined, at least partially, as being unable to afford tangible goods (and services) in a market-based economy,[79] then studies examining the impact of free good provision on health describe the effect of poverty reduction on health. Findings from these studies could then be considered alongside studies of other interventions aimed at reducing poverty, such as a basic income as a complementary approach to reducing poverty.[12, 13] Third, the free provision of goods could be understood as “non-cash” income that is valued similar to its cash equivalent after being appropriately discounted.[6] Fourth, having certain tangible goods can be understood as fulfilling a basic human right (e.g. the right to adequate housing, the right to adequate nutrition and clean water).[80] The provision of such goods could be seen as achieving social justice and could have positive impacts not only for individuals but also for their communities.
Comparison with prior studies
To the best of our knowledge this is the first systematic review to examine a wide range of free tangible goods and their effects on health. One recent systematic review and narrative analysis of 31 Housing First studies found mixed results for the impact of providing free housing for substance abuse and psychiatric symptoms, a clear benefit for housing stability, and a benefit for quality of life. These findings generally align well with ours. [81]
A number of studies have examined whether people who were given free goods use them or resell them. One such study conducted among pregnant women and households with young children in Uganda, for example, investigated this concept with the provision of free long-lasting insecticide treated mosquito nets. [82] This study assessed the willingness to pay for a mosquito net and willingness to sell a mosquito net given for free by simulating market exchanges. Seventy-three percent of people who received free nets were unwilling to accept the maximum price offered to part with even one of their nets. [82] Most people who were given free nets were not likely to resell their nets and in fact did use them for their intended purpose. [82]
Other studies have investigated using financial investments to complement health interventions and further improve health outcomes. A non-randomized controlled assessment from sub-Saharan Africa, in which simultaneous investments were made in agriculture, the environment, business development, education, infrastructure, and health in rural village sites with high baseline levels of poverty and under nutrition, found that mortality rates in young children decreased by 22% in study sites relative to baseline.[83] Reductions in poverty, food insecurity, stunting, and malaria parasitemia were also reported in study sites. [83]
Strengths and limitations of our study
Due to the great variety of free goods with potential to impact health, the design of a search strategy was challenging and we may have inadvertently omitted some key search terms. The wide array of interventions and outcomes meant that we could not perform a meta-analysis of results. The broad approach allowed us to include an interesting array of studies of different free tangible goods. Some studies involved co-interventions (e.g. almost all housing studies involved other supports in addition to free housing) and this limits the ability to determine whether the free good or the co-intervention affected health outcomes. We also excluded many studies that provided free tangible goods, including clean needles, condoms, and baby cribs, but did not report a health outcome. The literature may be biased towards studies of items with a less certain benefits. In other words, researchers may have decided not to study certain goods which are very likely to be beneficial (e.g. condoms, clean needles) and some such studies may not be ethical (i.e. it may be difficult to study the free provision of an item that is very likely to be beneficial). Some of the Housing First studies were overlapping as different reports included some of the same participants and some of the same outcomes, so we attempted to strike a balance between not excluding results and not counting the same results twice.
Conclusions and future work
Findings of this systematic review suggest that providing free tangible goods can promote health in certain circumstances. Additional high-quality studies of different goods are needed. Future work should also focus on the contexts in which free goods are most beneficial and explicitly state the theory or theories underpinning each study or intervention.
Acknowledgments
We thank Carolyn Ziegler with assistance designing and implementing the search strategy. We thank Anjli Bali for assistance obtaining articles. AP and NP are supported as Clinician Scientists by the Department of Family and Community Medicine, Faculty of Medicine, University of Toronto. AP is also supported by a fellowship from the Physicians’ Services Incorporated Foundation. NP is also supported by the Canada Research Chairs program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1. Wilkinson RG, Pickett KE. Income inequality and population health: A review and explanation of the evidence. Social Science & Medicine. 2006;62(7):1768–84. https://doi.org/10.1016/j.socscimed.2005.08.036.
- 2. Pickett KE, Wilkinson RG. Income inequality and health: A causal review. Social Science & Medicine. 2015;128:316–26. https://doi.org/10.1016/j.socscimed.2014.12.031.
- 3.
The World Health Organization. The determinants of health 2018. Available from: http://www.who.int/hia/evidence/doh/en/.
- 4.
The World Health Organization. Social determinants of health 2018. Available from: http://www.who.int/social_determinants/sdh_definition/en/.
- 5. Kemetmüller M, Leitner C, Moser M, Jérusalmy O, Storms B, Bosch KVd, et al. Handbook of Reference Budgets. 2009.
- 6. Callan T, Keane C. Non-Cash Benefits and the Distribution of Economic Welfare. The Institute for the Study of Labor (IZA). 2009;(3954).
- 7.
Malaria Campaign: Millions Receive Treated Mosquito Nets: The World Bank; 2011 [5 July 2018]. Available from: http://www.worldbank.org/en/news/feature/2011/04/24/malaria-campaign-millions-receive-treated-mosquito-nets.
- 8.
Needle Syringe Programs: Ontario Harm Reduction Distribution Program; 2018 [5 July 2018]. Available from: http://www.ohrdp.ca/about-us/needle-exchange/.
- 9.
Addressing Condom Supply and Demand in PEPFAR Programs 2017 [5 July 2018]. Available from: https://www.usaid.gov/what-we-do/global-health/hiv-and-aids/technical-areas/addressing-condom-supply-and-demand-pepfar.
- 10. Cameron ID, Kurrle S, Quine S, Sambrook P, March L, Chan D, et al. Increasing adherence with the use of hip protectors for older people living in the community. Osteoporosis International. 2011;22(2):617–26. pmid:20571769
- 11.
Dye C, Boerma T, Evans D, Harries A, Lienhardt C, McManus J, et al. Research for Universal Health Coverage. World Health Organization. 2013.
- 12. Beck S, Pulkki-Brännström A-M, San Sebastián M. Basic income–healthy outcome? Effects on health of an Indian basic income pilot project: a cluster randomised trial. Journal of Development Effectiveness. 2015;7(1):111–26.
- 13. Forget EL. The Town with No Poverty: The Health Effects of a Canadian Guaranteed Annual Income Field Experiment. Canadian Public Policy / Analyse de Politiques. 2011;37(3):283–305.
- 14. Henwood BF, Cabassa LJ, Craig CM, Padgett DK. Permanent Supportive Housing: Addressing Homelessness and Health Disparities? American Journal of Public Health. 2013;103(Suppl 2):S188–S92. PMC3908899. pmid:24148031
- 15.
Covidence systematic review software Melborne, Australia: Vertitas Health Innovation Ltd 2018 [5 July 2018]. Available from: https://www.covidence.org/.
- 16.
Cochrane Effective Practice and Organisation of Care (EPOC). Data collection form: Oslo: Norwegian Knowledge Centre for the Health Services; 2013. Available from: epoc.cochrane.org/epoc-resources-review-authors.
- 17. Higgins JPT, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343. pmid:22008217
- 18. Sterne JA, Hernán MA, Reeves BC, Savović J, Berkman ND, Viswanathan M, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016;355. pmid:27733354
- 19. Moher D, Liberati A, Tetzlaff J, Altman D, The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement.: PLoS Med; 2009.
- 20.
James FN, Umar S. The World Bank's classification of countries by income (English) Washington DC: World Bank Group; 2016. Available from: http://documents.worldbank.org/curated/en/408581467988942234/The-World-Banks-classification-of-countries-by-income
- 21. Tsemberis S, Gulcur L, Nakae M. Housing First, Consumer Choice, and Harm Reduction for Homeless Individuals With a Dual Diagnosis. American Journal of Public Health. 2004;94(4):651–6. pmid:15054020.
- 22. Stefancic A, Tsemberis S. Housing First for Long-Term Shelter Dwellers with Psychiatric Disabilities in a Suburban County: A Four-Year Study of Housing Access and Retention. The Journal of Primary Prevention. 2007;28(3):265–79. pmid:17592778
- 23. Padgett DK, Stanhope V, Henwood BF, Stefancic A. Substance Use Outcomes Among Homeless Clients with Serious Mental Illness: Comparing Housing First with Treatment First Programs. Community Mental Health Journal. 2011;47(2):227–32. pmid:20063061
- 24. Jacob BA, Ludwig J, Miller DL. The effects of housing and neighborhood conditions on child mortality. Journal of Health Economics. 2013;32(1):195–206. pmid:23202264
- 25. Montgomery A, Hill L, Kane V, Culhane S. HOUSING CHRONICALLY HOMELESS VETERANS: EVALUATING THE EFFICACY OF A HOUSING FIRST APPROACH TO HUD‐VASH. Journal of Community Psychology. 2013;41(5):505–14.
- 26. Patterson M, Moniruzzaman A, Palepu A, Zabkiewicz D, Frankish CJ, Krausz M, et al. Housing First improves subjective quality of life among homeless adults with mental illness: 12-month findings from a randomized controlled trial in Vancouver, British Columbia. Social Psychiatry and Psychiatric Epidemiology. 2013;48(8):1245–59. pmid:23748928
- 27. Palepu A, Patterson ML, Moniruzzaman A, Frankish CJ, Somers J. Housing First Improves Residential Stability in Homeless Adults With Concurrent Substance Dependence and Mental Disorders. American Journal of Public Health. 2013;103(S2):e30–e6. pmid:24148035.
- 28. Bean K, Shafer M, Glennon M. The impact of housing first and peer support on people who are medically vulnerable and homeless. Psychiatric Rehabilitation Journal 2013;36(1):48–50. pmid:23477651
- 29. Kessler RC, Duncan GJ, Gennetian LA, Katz LF, Kling JR, Sampson NA, et al. Associations of housing mobility interventions for children in high-poverty neighborhoods with subsequent mental disorders during adolescence. Jama. 2014;311(9):937–48. Epub 2014/03/07. pmid:24595778; PubMed Central PMCID: PMCPMC4100467.
- 30. Aubry T, Tsemberis S, Adair CE, Veldhuizen S, Streiner D, Latimer E, et al. One-year outcomes of a randomized controlled trial of housing first with ACT in five Canadian cities. Psychiatric services (Washington, DC). 2015;66(5):463–9. Epub 2015/02/03. pmid:25639993.
- 31. Kirst M, Zerger S, Misir V, Hwang S, Stergiopoulos V. The impact of a Housing First randomized controlled trial on substance use problems among homeless individuals with mental illness. Drug and Alcohol Dependence. 2015;146:24–9. pmid:25465295
- 32. Somers J, Moniruzzaman A, Palepu A. Changes in daily substance use among people experiencing homelessness and mental illness: 24‐month outcomes following randomization to Housing First or usual care. Addiction. 2015;110(10):1605–14. pmid:26052657
- 33. Stergiopoulos V, Gozdzik A, Misir V, Skosireva A, Connelly J, Sarang A, et al. Effectiveness of Housing First with Intensive Case Management in an Ethnically Diverse Sample of Homeless Adults with Mental Illness: A Randomized Controlled Trial. PLOS ONE. 2015;10(7):e0130281. pmid:26176621
- 34. Woodhall-Melnik J, Misir V, Kaufman-Shriqui V, O’Campo P, Stergiopoulos V, Hwang S. The Impact of a 24 Month Housing First Intervention on Participants’ Body Mass Index and Waist Circumference: Results from the At Home / Chez Soi Toronto Site Randomized Controlled Trial. PLOS ONE. 2015;10(9):e0137069. pmid:26418677
- 35. Kozloff N, Adair CE, Palma Lazgare LI, Poremski D, Cheung AH, Sandu R, et al. "Housing First" for Homeless Youth With Mental Illness. Pediatrics. 2016;138(4). Epub 2016/09/30. pmid:27681009.
- 36. Stergiopoulos V, Gozdzik A, Misir V, Skosireva A, Sarang A, Connelly J, et al. The effectiveness of a Housing First adaptation for ethnic minority groups: findings of a pragmatic randomized controlled trial. BMC Public Health. 2016;16(1):1110. pmid:27769226
- 37. Aubry T, Goering P, Veldhuizen S, Adair CE, Bourque J, Distasio J, et al. A Multiple-City RCT of Housing First With Assertive Community Treatment for Homeless Canadians With Serious Mental pmid:Illness. Psychiatric services (Washington, DC). 2016;67(3):275–81. Epub 2015/12/02.
- 38. Collins S, Taylor E, King V, Hatsukami A, Jones M, Lee C-Y, et al. Suicidality Among Chronically Homeless People with Alcohol Problems Attenuates Following Exposure to Housing First. Suicide and Life-Threatening Behavior. 2016;46(6):655–63. pmid:27061738
- 39. Somers JM, Moniruzzaman A, Patterson M, Currie L, Rezansoff SN, Palepu A, et al. A Randomized Trial Examining Housing First in Congregate and Scattered Site Formats. PLoS One. 2017;12(1):e0168745. Epub 2017/01/12. pmid:28076358; PubMed Central PMCID: PMCPMC5226665.
- 40. O'Campo P, Hwang SW, Gozdzik A, Schuler A, Kaufman-Shriqui V, Poremski D, et al. Food security among individuals experiencing homelessness and mental illness in the At Home/Chez Soi Trial. Public health nutrition. 2017;20(11):2023–33. Epub 2017/06/01. pmid:28560947.
- 41. Lee BJ, Mackey-Bilaver L. Effects of WIC and Food Stamp Program participation on child outcomes. Children and Youth Services Review. 2007;29(4):501–17. https://doi.org/10.1016/j.childyouth.2006.10.005.
- 42. Murphy JM, Pagano ME, Nachmani J, Sperling P, Kane S, Kleinman RE. The relationship of school breakfast to psychosocial and academic functioning: cross-sectional and longitudinal observations in an inner-city school sample. Archives of pediatrics & adolescent medicine. 1998;152(9):899–907. Epub 1998/09/22. pmid:9743037.
- 43. Gibson D. Food Stamp Program Participation is Positively Related to Obesity in Low Income Women. The Journal of Nutrition. 2003;133(7):2225–31. pmid:12840184
- 44. Gibson D. Long-Term Food Stamp Program Participation is Differentially Related to Overweight in Young Girls and Boys. The Journal of Nutrition. 2004;134(2):372–9. pmid:14747674
- 45. Ramirez-Lopez E, Grijalva-Haro MI, Valencia ME, Antonio Ponce J, Artalejo E. [Effect of a School Breakfast Program on the prevalence of obesity and cardiovascular risk factors in children]. Salud publica de Mexico. 2005;47(2):126–33. Epub 2005/05/14. pmid:15889638.
- 46. Gleason PM, Dodd AH. School breakfast program but not school lunch program participation is associated with lower body mass index. Journal of the American Dietetic Association. 2009;109(2 Suppl):S118–28. Epub 2009/03/17. pmid:19166666.
- 47. Arsenault JE, Mora-Plazas M, Forero Y, López-Arana S, Marín C, Baylin A, et al. Provision of a School Snack Is Associated with Vitamin B-12 Status, Linear Growth, and Morbidity in Children from Bogotá, Colombia. The Journal of Nutrition. 2009;139(9):1744–50. PMC3151021. pmid:19587125
- 48. Ask AS, Hernes S, Aarek I, Vik F, Brodahl C, Haugen M. Serving of free school lunch to secondary-school pupils—a pilot study with health implications. Public health nutrition. 2010;13(2):238–44. Epub 2009/08/05. pmid:19650962.
- 49. Ni Mhurchu C, Turley M, Gorton D, Jiang Y, Michie J, Maddison R, et al. Effects of a free school breakfast programme on school attendance, achievement, psychosocial function, and nutrition: a stepped wedge cluster randomised trial. BMC Public Health. 2010;10:738. Epub 2010/12/01. pmid:21114862; PubMed Central PMCID: PMCPMC3009648.
- 50. Chen Z, Zhang Q. Nutrigenomics Hypothesis: Examining the Association Between Food Stamp Program Participation and Bodyweight Among Low-Income Women. Journal of Family and Economic Issues. 2011;32(3):508–20.
- 51. Leung CW, Villamor E. Is participation in food and income assistance programmes associated with obesity in California adults? Results from a state-wide survey. Public health nutrition. 2011;14(4):645–52. Epub 2010/08/13. pmid:20701819.
- 52. Jilcott SB, Liu H, Dubose KD, Chen S, Kranz S. Food stamp participation is associated with fewer meals away from home, yet higher body mass index and waist circumference in a nationally representative sample. Journal of nutrition education and behavior. 2011;43(2):110–5. Epub 2011/03/12. pmid:21392714.
- 53. Nicholas LH. Can Food Stamps help to reduce Medicare spending on diabetes? Economics and human biology. 2011;9(1):1–13. Epub 2010/11/30. pmid:21112260; PubMed Central PMCID: PMCPMC3032985.
- 54. Schmeiser MD. The impact of long-term participation in the supplemental nutrition assistance program on child obesity. Health economics. 2012;21(4):386–404. Epub 2011/02/10. pmid:21305645.
- 55. Leung CW, Blumenthal SJ, Hoffnagle EE, Jensen HH, Foerster SB, Nestle M, et al. Associations of food stamp participation with dietary quality and obesity in children. Pediatrics. 2013;131(3):463–72. Epub 2013/02/27. pmid:23439902; PubMed Central PMCID: PMCPMC3581840.
- 56. Bere E, Klepp KI, Overby NC. Free school fruit: can an extra piece of fruit every school day contribute to the prevention of future weight gain? A cluster randomized trial. Food & nutrition research. 2014;58. Epub 2014/08/26. pmid:25147495; PubMed Central PMCID: PMCPMC4131001.
- 57. McMahon DM, Vdovenko VY, Stepanova YI, Karmaus W, Zhang H, Irving E, et al. Dietary supplementation with radionuclide free food improves children's health following community exposure to (137)Cesium: a prospective study. Environmental health: a global access science source. 2015;14:94. Epub 2015/12/23. pmid:26689948; PubMed Central PMCID: PMCPMC4687105.
- 58. Davies GM, Worthington HV, Ellwood RP, Bentley EM, Blinkhorn AS, Taylor GO, et al. A randomised controlled trial of the effectiveness of providing free fluoride toothpaste from the age of 12 months on reducing caries in 5–6 year old children. Community dental health. 2002;19(3):131–6. Epub 2002/09/25. pmid:12269458.
- 59. Boisson S, Stevenson M, Shapiro L, Kumar V, Singh LP, Ward D, et al. Effect of Household-Based Drinking Water Chlorination on Diarrhoea among Children under Five in Orissa, India: A Double-Blind Randomised Placebo-Controlled Trial. PLOS Medicine. 2013;10(8):e1001497. pmid:23976883
- 60. Nicholson JA, Naeeni M, Hoptroff M, Matheson JR, Roberts AJ, Taylor D, et al. An investigation of the effects of a hand washing intervention on health outcomes and school absence using a randomised trial in Indian urban communities. Tropical Medicine and International Health 2014;19(3):284–92. pmid:24382344
- 61. Luby SP, Agboatwalla M, Painter J, Altaf A, Billhimer W, Keswick B, et al. Combining drinking water treatment and hand washing for diarrhoea prevention, a cluster randomised controlled trial. Tropical Medicine & International Health. 2006;11(4):479–89. pmid:16553931
- 62. Livny A, Sgan-Cohen HD. A review of a community program aimed at preventing early childhood caries among Jerusalem infants—a brief communication. Journal of public health dentistry. 2007;67(2):78–82. Epub 2007/06/15. pmid:17557677.
- 63. Das LK, Harichandrakumar KT, Vijayalakshmi G, De Britto LJ. Effect of domiciliary limb hygiene alone on lymphoedema volume and locomotor function in filarial lymphoedema patients in Puducherry, India. The Journal of communicable diseases. 2013;45(1–2):17–23. Epub 2013/03/01. pmid:25141550.
- 64.
Browne E, H Maude G, Binka F. The impact of insecticide-treated bednets on malaria and anaemia in pregnancy in Kassena-Nankana district, Ghana: A randomized controlled trial2001. 667–76 p.
- 65. Fegan GW, Noor AM, Akhwale WS, Cousens S, Snow RW. Effect of expanded insecticide-treated bednet coverage on child survival in rural Kenya: a longitudinal study. Lancet (London, England). 2007;370(9592):1035–9. PMC2117339. pmid:17889242
- 66.
Fokam E, Ngimuh L, Anchang J, Wanji S. Assessment of the usage and effectiveness of intermittent preventive treatment and insecticide-treated nets on the indicators of malaria among pregnant women attending antenatal care in the Buea Health District, Cameroon2016.
- 67. Anyaehie U, Nwagha UI, Aniebue PN, Nwagha TU. The effect of free distribution of insecticide-treated nets on asymptomatic Plasmodium parasitemia in pregnant and nursing mothers in a rural Nigerian community. Nigerian journal of clinical practice. 2011;14(1):19–22. Epub 2011/04/16. pmid:21493986.
- 68. Apinjoh TO, Anchang-Kimbi JK, Mugri RN, Tangoh DA, Nyingchu RV, Chi HF, et al. The effect of Insecticide Treated Nets (ITNs) on Plasmodium falciparum infection in rural and semi-urban communities in the south west region of Cameroon. PLoS One. 2015;10(2):e0116300. Epub 2015/02/26. pmid:25714837; PubMed Central PMCID: PMCPMC4340618.
- 69. DiGuiseppi C, Roberts I, Wade A, Sculpher M, Edwards P, Godward C, et al. Incidence of fires and related injuries after giving out free smoke alarms: cluster randomised controlled trial. Bmj. 2002;325(7371):995. Epub 2002/11/02. pmid:12411355; PubMed Central PMCID: PMCPMC131023.
- 70. Mallonee S. Evaluating Injury Prevention Programs: The Oklahoma City Smoke Alarm Project2000. 164–74 p.
- 71. O'Halloran PD, Cran GW, Beringer TRO, Kernohan G, O'Neill C, Orr J, et al. A cluster randomised controlled trial to evaluate a policy of making hip protectors available to residents of nursing homes. Age and Ageing. 2004;33(6):582–8. pmid:15381506
- 72. Watson M, Kendrick D, Coupland C, Woods A, Futers D, Robinson J. Providing child safety equipment to prevent injuries: randomised controlled trial. BMJ. 2005;330(7484):178. pmid:15604156
- 73. Zadik Y, Levin L. Does a free-of-charge distribution of boil-and-bite mouthguards to young adult amateur sportsmen affect oral and facial trauma? Dental Traumatology. 2009;25:69–72. pmid:19208013
- 74. Nyomba BL, Berard L, Murphy LJ. Facilitating access to glucometer reagents increases blood glucose self-monitoring frequency and improves glycaemic control: a prospective study in insulin-treated diabetic patients. Diabetic medicine: a journal of the British Diabetic Association. 2004;21(2):129–35. Epub 2004/02/27. pmid:14984447.
- 75. Guo H, Tian X, Li R, Jin N, Wu Z, Yu D. Reward-based, task-setting education strategy on glycemic control and self-management for low-income outpatients with type 2 diabetes Jourmal of Diabetes Investigation. 2014;5:410–7. pmid:25411600
- 76. Lund S, Rasch V, Hemed M, Boas IM, Said A, Said K, et al. Mobile Phone Intervention Reduces Perinatal Mortality in Zanzibar: Secondary Outcomes of a Cluster Randomized Controlled Trial. JMIR mHealth and uHealth. 2014;2(1):e15. PMC4114456. pmid:25098184
- 77. Nicol I, Gaudy C, Gouvernet J, Richard MA, Grob JJ. Skin protection by sunscreens is improved by explicit labeling and providing free sunscreen. The Journal of investigative dermatology. 2007;127(1):41–8. Epub 2006/10/28. pmid:17068486.
- 78. Webb E, Netuveli G, Millett C. Free bus passes, use of public transport and obesity among older people in England. Journal of epidemiology and community health. 2012;66(2):176–80. Epub 2011/09/14. pmid:21911850.
- 79. Storms B, Goedemé T, Bosch KVd, Penne T, Schuerman N, Stockman S. Pilot project for the development of a common methodology on reference budgets in Europe. European Comission, 2014.
- 80.
United Nations General Assembly. Universal Declaration of Human Rights Paris: 1948 Contract No.: 217 (III) A.
- 81. Woodhall-Melnik JR, Dunn JR. A systematic review of outcomes associated with participation in Housing First programs. Housing Studies. 2016;31(3):287–304.
- 82. Hoffmann V, Barrett CB, Just DR. Do Free Goods Stick to Poor Households? Experimental Evidence on Insecticide Treated Bednets. World Development. 2009;37(3):607–17. https://doi.org/10.1016/j.worlddev.2008.08.003.
- 83. Pronyk PM, Muniz M, Nemser B, Somers M-A, McClellan L, Palm CA, et al. The effect of an integrated multisector model for achieving the Millennium Development Goals and improving child survival in rural sub-Saharan Africa: a non-randomised controlled assessment. The Lancet. 2012;379(9832):2179–88. https://doi.org/10.1016/S0140-6736(12)60207-4.