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The Spreading of Cohabitation as a Diffusion Process: Evidence from Italy.

ABSTRACT: Drawing on seminal work by Nazio and Blossfeld (Eur J Popul 19(1):47-82, 2003) and Di Giulio and Rosina (Demogr Res 16(14):441-468, 2007), this paper tests whether the recent spread of cohabitation in Italy has followed the typical pattern of diffusion of innovation processes. In doing so, we contribute to the debate on the determinants of the emergence of "new" family behaviour. Following previous literature, innovative behaviour should spread initially through direct social modelling, i.e. interpersonal communication among highly selected individuals (peer effects). At later stages, the diffusion should spread through knowledge awareness of the innovation, i.e. communication with previous generations (pre-cohort effects), so that also less selected individuals are prone to adopt the new behaviour. In the specific Italian context-a Catholic, "familistic" setting, with high normative pressure and importance of parental approval-we surmise the influence of previous generations to be dominant. We use data from the "Family and Social Subjects" survey carried out by Istat (2009) and apply Event History Analysis in the form of competing-risks exponential models to study Italian women's transition to cohabitation as first partnership. Results suggest that the most important driver of the spreading of cohabitation in Italy is represented by the degree of its diffusion among older cohorts. However, we find a positive and significant interaction between women's education and peer effects at the onset of the phenomenon, in line with the Second Demographic Transition (SDT) hypothesis. Cohabitation is also more likely if parents experienced separation/divorce and, more generally, if the environment of the family of origin can be described as "SDT-friendly".

SUBMITTER: Guetto R

PROVIDER: S-EPMC6241092 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesA number of studies have shown that the airborne transmission route could spread some viruses over a distance of 2 meters from an infected person. An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of COVID-19 in Italy. On March 16th 2020, we presented a position paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and average concentrations of PM10 exceeding a daily limit of 50 µg/m3.MethodsTo monitor the spreading of COVID-19 in Italy from February 24th to March 13th (the date of the Italian lockdown), official daily data for PM10 levels were collected from all Italian provinces between February 9th and February 29th, taking into account the maximum lag period (14 days) between the infection and diagnosis. In addition to the number of exceedances of the daily limit value of PM10, we also considered population data and daily travelling information for each province.ResultsExceedance of the daily limit value of PM10 appears to be a significant predictor of infection in univariate analyses (p<0.001). Less polluted provinces had a median of 0.03 infections over 1000 residents, while the most polluted provinces showed a median of 0.26 cases. Thirty-nine out of 41 Northern Italian provinces resulted in the category with the highest PM10 levels, while 62 out of 66 Southern provinces presented low PM10 concentrations (p<0.001). In Milan, the average growth rate before the lockdown was significantly higher than in Rome (0.34 vs 0.27 per day, with a doubling time of 2.0 days vs 2.6, respectively), thus suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China.ConclusionA significant association has been found between the geographical distribution of daily PM10 exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.

Project description:COVID-19 (coronavirus disease 2019) has spread successfully worldwide in a matter of weeks. After the example of China, all the affected countries are taking hard-confinement measures to control the infection and to gain some time to reduce the significant amount of cases that arrive at the hospital. Although the measures in China reduced the percentages of new cases, this is not seen in other countries that have taken similar measures, such as Italy and Spain. After the first weeks, the worry was whether or not the healthcare system would collapse rather than its response to the patient's needs who are infected and require hospitalization. Using China as a mirror of what could happen in our countries and with the data available, we calculated a model that forecasts the peak of the curve of infection, hospitalization, and ICU bed numbers. We aimed to review the patterns of spread of the virus in the two countries and their regions, looking for similarities that reflect the existence of a typical path in this expansive virulence and the effects of the intervention of the authorities with drastic isolation measures, to contain the outbreak. A model based on Autorregressive and moving average models (ARMA) methodology and including Chinese disease pattern as a proxy, predicts the contagious pattern robustly. Based on the prediction, the hospitalization and intensive care unit (ICU) requirements were also calculated. Results suggest a reduction in the speed of contagion during April in both countries, earlier in Spain than in Italy. The forecast advanced a significant increase in the ICU needs for Spain surpassing 8,000 units by the end of April, but for Italy, ICU needs would decrease in the same period, according to the model. We present the following predictions to inform political leaders because they have the responsibility to maintain the national health systems away from collapsing. We are confident these data could help them into decision-taking and place the capitals (from hospital beds to human resources) into the right place.

Project description:Marriage is associated with better mental health. While research on the mental health of cohabiting individuals has increased in recent years, it has yielded mixed results thus far. We assessed whether the mental health of cohabiters is comparable to that of married individuals or those living alone using longitudinal data on psychotropic medication purchases. Panel data from an 11% random sample of the population residing in Finland for the years 1995 to 2007, with annual measurements of all covariates, were used. Ordinary least squares (OLS) models were applied to disentangle the relation between cohabitation and psychotropic medication purchases while controlling for relevant time-varying factors (age, education, economic activity, and number of children), and individual fixed effects (FE) models to further account for unobserved time-invariant individual factors. Our sample consisted of 63,077 men and 61,101 women aged 25 to 39 years in 1995. Descriptive results and the OLS model indicated that the likelihood of purchasing psychotropic medication was lowest for married individuals, higher for cohabiters, and highest for individuals living alone. This difference between cohabiting and married individuals disappeared after controlling for time-varying covariates (percent difference [% diff] for men: 0.3, 95% confidence interval [CI]: -0.0, 0.6; % diff for women: -0.2, 95% CI: -0.6, 0.2). Further controlling for unobserved confounders in the FE models did not change this non-significant difference between cohabiting and married individuals. The excess purchases of psychotropic medication among individuals living alone compared to those cohabiting decreased to 1.2 (95% CI: 1.0, 1.4) and 1.4 (95% CI: 1.1, 1.6) percentage-points in the fully-adjusted FE model for men and women, respectively. Similar results were found for all subcategories of psychotropic medication. In summary, these findings suggested that the mental health difference between cohabiting and married individuals, but not the difference between cohabiting individuals and those living alone, was largely due to selection.

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The Spreading of Cohabitation as a Diffusion Process: Evidence from Italy.

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