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I used data from 12,340 respondents to the 2018 China General Social Survey to explore the relationship of Chinese residents' socioeconomic status (SES) with depression and well-being. I performed multiple linear regression analyses with depression and well-being in life as dependent variables and SES as the independent variable to explore the relationships among the above variables and the differences in these relationships in terms of gender and residence in an urban versus rural area. The results showed that SES was significantly and negatively correlated with depression and significantly and positively correlated with well-being in life. In other words, the higher the SES, the lower the level of depression and the greater the well-being in life. In addition, the relationship between SES and depression varied according to gender, with SES more prominently associated with depression in women; however, the effect of gender was nonsignificant in the relationship between SES and well-being in life. Similarly, living in an urban or rural area did not have a significant influence on the association of SES with depression and well-being in life. These findings add to understanding of SES in relation to depression and wellbeing in life among people in China.

This paper investigates the intergenerational transmission of risk attitudes in the context of a low income country with a focus on rural–urban and gender differences. Our empirical analysis is based on a household survey completed in Burkina Faso in 2014 which asks family members about their willingness to take risk in various domains. We find a positive correlation between parental and child risk attitudes, which is higher for risk in driving and risk in general than for risk in finance. For risk in driving and risk in general, the parent-child correlation is lower in rural area than in urban area. Also, we evidence gender-specific effects of parental risk attitudes. The intergenerational correlation in risk attitudes is higher for daughters than for sons, the father–daughter correlation is lower than the father–son correlation and the mother–daughter correlation is higher than the mother–son correlation.

Background Most studies of chronic kidney disease (CKD) in Sub-Saharan Africa (SSA) have been conducted in urban settings. They relied on GFR estimated from serum creatinine alone and on the inexpensive, convenient urinary dipstick to assess proteinuria. The dipstick for proteinuria has not been directly compared with the gold standard albumin-to-creatinine ratio (ACR) in a large-sized study in SSA. We hereby assessed the influence of rural versus urban location on the level, interpretation, and diagnostic performance of proteinuria dipstick versus ACR. Methods In a cross-sectional population-based study of CKD in both urban ( n  = 587) and rural ( n  = 730) settings in South-Kivu, Democratic Republic of Congo (DRC), we assessed the prevalence, performance (sensitivity, specificity, positive predictive value and negative predictive value) and determinants of a positive dipstick proteinuria as compared with albuminuria (ACR). Albuminuria was subdivided into: A1 (< 30 mg/g creatinine), A2 (30 to 299 mg/g creatinine) and A3 (≥ 300 mg/g creatinine). Results The overall prevalence of positive dipstick proteinuria (≥ 1+) was 9.6 % (95 % CI, 7.9–11.3) and was higher in rural than in urban residents (13.1 % vs. 4.8 %, p  < 0.001), whereas the prevalence of albuminuria (A2 or A3) was similar in both sites (6 % rural vs. 7.6 % urban, p  = 0.31). In both sites, dipstick proteinuria ≥ 1 + had a poor sensitivity (< 50 %) and positive predictive value (< 11 %) for the detection of A2 or A3. The negative predictive value was 95 %. Diabetes [aOR 6.12 (1.52–24.53)] was a significant predictor of A3 whereas alkaline [aOR 7.45 (3.28–16.93)] and diluted urine [aOR 2.19 (1.35–3.57)] were the main predictors of positive dipstick proteinuria. Conclusions ACR and dipstick proteinuria have similar positivity rates in the urban site whereas, in the rural site, dipstick was 2-fold more often positive than ACR. The poor sensitivity and positive predictive value of the dipstick as compared with ACR makes it unattractive as a screening tool in community studies of CKD in SSA.

Despite recent decline in hospital acquired conditions (HACs), rates for pressure ulcers (PURs) and falls (FRs) remain at levels that require improvement. Contextual factors and care processes may impact HACs. Using the National Database of Nursing Quality Indicators (NDNQI®) this study examined differences in care processes and community, hospital, and nursing unit characteristics that influence PURs and FRs in 4238 rural and urban nursing units. This article reports on the study methods, noting results that demonstrated differences across all characteristics. The discussion considers the findings and implications in the context of rural or urban location. Many areas identified may be useful to implement multilevel improvement strategies tailored specifically to a rural or urban hospital.

Territorial User Rights in Fisheries (TURFs) have spread in Chile, since the late 1990s, in the form of commons institutions. TURFs are presented by some scholars as a social-ecological success; by others as showing economic and compliance problems. Studies looking at the material conditions in which fishers produce and reproduce their livelihoods, and in which TURFs emerge, are scarcer. Ostrom’s theory on the commons claims that certain collective action conditions have to be met to become thriving commons institutions. Our hypothesis is that while institutions are moulded by local material conditions, such as geographical location and social embeddedness, these impose challenges and constraints upon fishers influencing TURFs’ long-term viability. How are collective action conditions influenced when the new TURFs commons do not emerge in tabula rasa contexts but in occupied spaces? Do material conditions influence TURFs’ sustainability? This paper set out to explore these conditions. Huentelauquén’s and Guayacán’s TURFs (central-northern Chile) were chosen, as they represent two extremes (rural-urban; on private property-on State/municipal property; mainly diver – mainly fisher) contexts in which TURFs have emerged. We mainly used Participatory Rural Approach (PRA) tools triangulated with other qualitative methods. This study shows that both social embeddedness (private/State lands), and geographical location (rural/urban) matter, resulting in different access to the coast for different TURFs, thus determining some important differences between our cases in at least three relevant areas: entrance, social relations between the fishers’ organization (entitled the TURFs) and the landowner (private or municipal/State) and the existence or absence of fishing and general infrastructure. Competition for space among key actors seems to affect the process of acquiring a TURF as well as the conditions conductive to collective action. TURFs’ assessments should therefore consider both, the local particularities of specific fishing communities and the larger structural context in which they emerge, that if not paid attention to, can weakens TURFs’ viability for sustainable fisheries.

Metropolitan areas worldwide have grown rapidly and are usually surrounded by peri-urban zones that are neither urban nor rural. Despite widespread use of the term ‘peri-urban’, physical determination of these spaces is difficult due to their transient nature and multiple definitions. While many have identified peri-urban areas regionally or globally, questions persist on where exactly the peri-urban is located, and what are the most apt methods to delineate its boundaries. The answers are pertinent towards framing targeted policies for governing the dynamic socio-spatial transformations in these zones. This paper reviews peri-urban research over the last 50-plus years to discern the existing methodologies for its identification/demarcation and their applications. For this, a total of 3124 documents on peri-urban studies were identified through keyword searches in Scopus and Google Scholar databases. Thereafter, 56 documents were examined that explicitly dealt with demarcating peri-urban zones. Results reveal that there is no standout/generalized method for peri-urban demarcation. Rather, these approaches are geographically specific and vary across developed and developing countries, due to differences in land-use patterns, socioeconomic drivers, and political systems. Thus, we recommend developing a ‘pluralistic’ framework for determining peri-urban boundaries at the regional–global scale to enable better framing of relevant policies.

Today, over half of the world’s population lives in urban areas and it is projected that, by 2050, two out of three people will live in a city. This increased rural–urban migration, coupled with housing poverty, has led to the growth and formation of informal settlements, commonly known as slums. In Mexico, 25% of the urban population now live in informal settlements with varying degrees of deprivation. Although some informal neighbourhoods have contributed to the upward mobility of the inhabitants, the majority still lack basic services. Mexico City and the conurbation around it form a mega city of 21million people that has been growing in a manner qualified as ‘highly unproductive, (that) deepens inequality, raises pollution levels’ (available at: https://www.smartcitiesdive.com/ex/sustainablecitiescollective/making-way-urban-reform-mexico/176466/) and contains the largest slum in the world: Neza-Chalco-Izta. Urban reforms are now aiming to improve the conditions in these slums and therefore it is very important to have reliable tools to measure the changes that are underway. In this paper, we use exploratory factor analysis to define an index of shelter deprivation in Mexico City, namely the Slum Severity Index (SSI), based on the UN-HABITAT’s definition of slum. We apply this novel approach to the Census survey of Mexico and measure the shelter deprivation levels of households from 1990 to 2010. The analysis highlights high variability in housing conditions within Mexico City. We find that the SSI decreased significantly between 1990 and 2000 as a result of several policy reforms but increased between 2000 and 2010. We also show correlations of the SSI with other social factors such as education, health and fertility. We present a validation of the SSI using Grey Level Co-occurrence Matrix (GLCM) features extracted from Very-High Resolution (VHR) remote-sensed satellite images. Finally, we show that the SSI can present a cardinally meaningful assessment of the extent of deprivation compared with a similar index defined by Connolly (Connolly P (2009) Observing the evolution of irregular settlements: Mexico city’s colonias populares, 1990 to 2005. International Development Planning Review 31: 1–35) that studies shelter deprivation in Mexico. 如今，超过一半的世界人口生活在城市地区，预计到2050年，三分之二的人口将生活在城市。越来越多的乡村到城市移民加上住房贫困，导致了非正规住区的增长和形成，它们通常被称为贫民窟。在墨西哥，目前25%的城市人口生活在不同程度贫困的非正规住区。尽管一些非正规住区促进了居民的向上流动，但大多数居民仍然缺乏基本服务。墨西哥城及其周围的大都市区形成了一个拥有2,100万人口的巨型城市，其增长方式属于“加剧不平等和污染水平的高生产率”（可在以下网站查阅： https://www.smartcitiesdive.com/ex/sustainablecitiescollective/making-way-urban-reform-mexico/176466/），并包括世界上最大的贫民窟那扎-查可-伊泽塔(Neza-Chalco-Izta)。城市改革的目标是改善这些贫民窟的条件，因此拥有可靠的工具来衡量正在发生的变化非常重要。在本文中，我们根据联合国人居署对贫民窟的定义，使用探索性因素分析来定义墨西哥城的住房匮乏指数，即贫民窟严重程度指数(SSI)。我们将这一新方法应用于墨西哥的人口普查，并测量了1990年至2010年期间家庭住房匮乏的程度。我们的分析凸显了墨西哥城住房条件的高度可变性。我们发现，由于若干政策改革，SSI在1990年至2000年期间大幅下降，但在2000年至2010年期间有所上升。我们还揭示了SSI与教育、健康和生育率等其他社会因素的相关性。我们利用从超高分辨率(VHR)遥感卫星图像中提取的灰度共生矩阵(GLCM)特征对SSI进行了验证。最后，我们证明，与康纳利定义的类似指数（Connolly P (2009) Observing the evolution of irregular settlements: Mexico city’s colonias populares, 1990 to 2005.International Development Planning Review 31:1-35）相比，SSI可以对贫困程度进行具有最重大意义的评估。

Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Without a clear understanding of the data representativeness, the interpretations of research based on mobile location data may be questionable. This article presents a comprehensive examination of the potential biases associated with mobile location data using SafeGraph Patterns data in the United States as a case study. The research rigorously scrutinizes and documents the bias from multiple dimensions, including spatial, temporal, urbanization, demographic, and socioeconomic, over a five-year period from 2018 to 2022 across diverse geographic levels, including state, county, census tract, and census block group. Our analysis of the SafeGraph Patterns dataset revealed an average sampling rate of 7.5% with notable temporal dynamics, geographic disparities, and urban-rural differences. The number of sampled devices was strongly correlated with the census population at the county level over the five years for both urban (r > 0.97) and rural counties (r > 0.91), but less so at the census tract and block group levels. We observed minor sampling biases among groups such as gender, age, and moderate-income, with biases typically ranging from -0.05 to +0.05. However, minority groups such as Hispanic populations, low-income households, and individuals with low levels of education generally exhibited higher levels of underrepresentation bias that varied over space, time, urbanization, and across geographic levels. These findings provide important insights for future studies that utilize SafeGraph data or other mobile location datasets, highlighting the need to thoroughly evaluate the spatiotemporal dynamics of the bias across spatial scales when employing such data sources.

Empirical evidence describes the negative outcomes people with mental health disorders experience due to societal stigma. The aim of this study was to examine the role of gender and rural-urban living in perceptions about mental illness. Participants completed the Day’s Mental Illness Stigma Scale, a nationally validated instrument for measuring stigma. Directors of Chambers of Commerce in North Dakota distributed the electronic survey to their members. Additionally, distribution occurred through use of social media and other snowball sampling approaches. Analysis of data gathered from 749 participants occurred through examination of the difference in perceptions based on geography and gender. The zip codes of residence were sorted to distinguish between rural and urban participants. Application of weighting measures ensured closer alignment with the general population characteristics. Findings indicate that for the majority of the seven stigma measures the Day’s Mental Illness Stigma Scale examines, the coefficient of rural–gender interactions was positive and highly significant with higher levels of stigma in rural areas. Females exhibited lower stigma perceptions than males. However, women living in rural areas held higher degrees of stigma compared to urban residing females. Implications of the study include the need to advance mental health literacy campaigns for males and people residing in rural communities. Additional empirical studies that examine the role of geography and gender in understanding stigma toward people with mental health disorders will result in improved treatment outcomes due to increased and focused educational efforts.

Research examining how youth substance use is associated with both proximal microsystemic processes (interactions with family members) and distal macrosystemic conditions (rurality) is limited. To address this gap, a person-/variable-centered approach was used to: (1) identify latent profiles of family risk and protective factors for substance use, (2) test profile membership as a predictor of lifetime and 30-day substance use, (3) test rurality, as measured by school geographic location, as a predictor, and (4) explore interaction effects between profile membership and rurality. Youth ( N  = 9,104; 53% female) residing in a state in the southeastern U.S. completed a statewide substance abuse and risk behavior survey including questions about family risk and protective factors and substance use behaviors. Using latent profile analysis to identify subgroups of participants with similar means and variances on the family factors, four latent profiles emerged. Risk of 30-day and lifetime substance use varied across profiles, with the profile characterized by high family-level protective factors and low family-level risk factors indicating the lowest risk for substance use. Urban youth had increased odds of reporting lifetime marijuana use compared to suburban youth; however, geographic location did not appear to confer significantly increased or decreased risk across other substances. No significant interaction results were found. These results emphasize the importance of family functioning on substance use regardless of geographic location, and that evidence-based prevention programming that reduces family risk, strengthens family protection, and is accessible to all types of communities is important to reducing or delaying substance use among youth. Highlights Families supporting prosocial behavior, appropriately supervising, and limiting conflict protected youth from substance use. School geographic location was not a significant predictor of odds of substance use among youth. Families and youth in all communities would benefit from access to family-based prevention to reduce substance use.