Since , the economy has added In , young workers with a high school diploma had roughly triple the unemployment rate and three and a half times the poverty rate of college grads. Once you start tracing these trends backward, the recession starts to look less like a temporary setback and more like a culmination. Over the last 40 years, as politicians and parents and perky magazine listicles have been telling us to study hard and build our personal brands, the entire economy has transformed beneath us.
For decades, most of the job growth in America has been in low-wage, low-skilled, temporary and short-term jobs. The United States simply produces fewer and fewer of the kinds of jobs our parents had. The decline of the job has its primary origins in the s, with a million little changes the boomers barely noticed. The Federal Reserve cracked down on inflation. Companies started paying executives in stock options.
Pension funds invested in riskier assets.
The cumulative result was money pouring into the stock market like jet fuel. Between and , the average time that investors held stocks before flipping them went from eight years to around four months. The pressure to deliver immediate returns became relentless. The new paradigm took over corporate America. Private equity firms and commercial banks took corporations off the market, laid off or outsourced workers, then sold the businesses back to investors. In the s alone, a quarter of the companies in the Fortune were restructured. Companies were no longer single entities with responsibilities to their workers, retirees or communities.
Businesses applied the same chop-shop logic to their own operations. Executives came to see themselves as first and foremost in the shareholder-pleasing game.
Higher staff salaries became luxuries to be slashed. Unions, the great negotiators of wages and benefits and the guarantors of severance pay, became enemy combatants. And eventually, employees themselves became liabilities. Thirty years ago, she says, you could walk into any hotel in America and everyone in the building, from the cleaners to the security guards to the bartenders, was a direct hire, each worker on the same pay scale and enjoying the same benefits as everyone else.
Since the downturn, the industry that has added the most jobs is not tech or retail or nursing. This transformation is affecting the entire economy, but millennials are on its front lines. Where previous generations were able to amass years of solid experience and income in the old economy, many of us will spend our entire working lives intermittently employed in the new one.
Trade groups have responded to the dwindling number of secure jobs by digging a moat around the few that are left. It makes sense: The harder it is to become a plumber, the fewer plumbers there will be and the more each of them can charge. Nearly a third of American workers now need some kind of state license to do their jobs, compared to less than 5 percent in It was supposed to be training, but she says she worked the same hours and did the same tasks as paid staffers. All of these trends—the cost of education, the rise of contracting, the barriers to skilled occupations—add up to an economy that has deliberately shifted the risk of economic recession and industry disruption away from companies and onto individuals.
For our parents, a job was a guarantee of a secure adulthood. For us, it is a gamble.
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I heard the most acute description of how this happens from Anirudh Krishna, a Duke University professor who has, over the last 15 years, interviewed more than 1, people who fell into poverty and escaped it. He started in India and Kenya, but eventually, his grad students talked him into doing the same thing in North Carolina. The mechanism, he discovered, was the same. We often think of poverty in America as a pool, a fixed portion of the population that remains destitute for years. In fact, Krishna says, poverty is more like a lake, with streams flowing steadily in and out all the time.
Between and , the probability that a working-age American would unexpectedly lose at least half her family income more than doubled. And the danger is particularly severe for young people. In the s, when the boomers were our age, young workers had a 24 percent chance of falling below the poverty line. By the s, that had risen to 37 percent. And the numbers only seem to be getting worse.
From to , the poverty rate among young workers with only a high school diploma more than tripled, to 22 percent. Gabriel is 19 years old and lives in a small town in Oregon. He plays the piano and, until recently, was saving up to study music at an arts college. Last summer he was working at a health supplement company. Then his sister got into a car accident, T-boned turning into their driveway. His mom wasn't able to take a day off without risking losing her job, so Gabriel called his boss and left a message saying he had to miss work for a day to get his sister home from the hospital.
The next day, his temp agency called: He was fired. Though Gabriel says no one had told him, the company had a three-strikes policy for unplanned absences. He had already missed one day for a cold and another for a staph infection, so this was it. A former colleague told him that his absences meant he was unlikely to get a job there again. So now Gabriel works at Taco Time and lives in a trailer with his mom and his sisters. He still wants to go to college. The answer is brutally simple. In an economy where wages are precarious and the safety net has been hacked into ribbons, one piece of bad luck can easily become a years-long struggle to get back to normal.
Over the last four decades, there has been a profound shift in the relationship between the government and its citizens. Even Richard Nixon, not exactly known for lifting up the downtrodden, proposed a national welfare benefit and a version of a guaranteed income. It became individualized, a duty to earn the benefits your country offered you. Since , the percentage of poor families receiving cash assistance from the government has fallen from 68 percent to 23 percent. No state provides cash benefits that add up to the poverty line. Eligibility criteria have been surgically tightened, often with requirements that are counterproductive to actually escaping poverty.
Take Temporary Assistance for Needy Families, which ostensibly supports poor families with children. Its predecessor with a different acronym had the goal of helping parents of kids under 7, usually through simple cash payments. These days, those benefits are explicitly geared toward getting mothers away from their children and into the workforce as soon as possible. A few states require women to enroll in training or start applying for jobs the day after they give birth. The list goes on. Housing assistance, for many people the difference between losing a job and losing everything, has been slashed into oblivion.
To pick just one example, in Baltimore had 75, applicants for 1, rental vouchers. In what seems like some kind of perverse joke, nearly every form of welfare now available to young people is attached to traditional employment. The only major expansions of welfare since have been to the Earned Income Tax Credit and the Child Tax Credit, both of which pay wages back to workers who have already collected them. Back when we had decent jobs and strong unions, it kind of made sense to provide things like health care and retirement savings through employer benefits.
But now, for freelancers and temps and short-term contractors—i. In , 4 out of 5 employees got health insurance through their jobs. Now, just over half of them do. But the cohort right afterward, to year-olds, has the highest uninsured rate in the country and millennials—alarmingly—have more collective medical debt than the boomers.
Even Obamacare, one of the few expansions of the safety net since man walked on the moon, still leaves us out in the open. And of the events that precipitate the spiral into poverty, according to Krishna, an injury or illness is the most common trigger. For most of her clients under 35, she says, the slide toward bankruptcy starts with a car accident or a medical bill.
Then he gets sick of it and he fires you and it all gets worse. The wealth gap between white and non-white families is massive. Since basically forever, almost every avenue of wealth creation—higher education, homeownership, access to credit—has been denied to minorities through discrimination both obvious and invisible. And the disparity has only grown wider since the recession. The result is that millennials of color are even more exposed to disaster than their peers.
Many white millennials have an iceberg of accumulated wealth from their parents and grandparents that they can draw on for help with tuition, rent or a place to stay during an unpaid internship. According to the Institute on Assets and Social Policy, white Americans are five times more likely to receive an inheritance than black Americans—which can be enough to make a down payment on a house or pay off student loans. And so, instead of receiving help from their families, millennials of color are more likely to be called on to provide it.
Any extra income from a new job or a raise tends to get swallowed by bills or debts that many white millennials had help with. Four years after graduation, black college graduates have, on average, nearly twice as much student debt as their white counterparts and are three times more likely to be behind on payments. The median white household will have 10 15 16 69 86 more wealth than the median black household by Want to get even more depressed?
Despite all the stories you read about flighty millennials refusing to plan for retirement as if our grandparents were obsessing over the details of their pension plans when they were 25 , the biggest problem we face is not financial illiteracy. It is compound interest. In the coming decades, the returns on k plans are expected to fall by half. According to an analysis by the Employee Benefit Research Institute, a drop in stock market returns of just 2 percentage points means a year-old would have to contribute more than double the amount to her retirement savings that a boomer did.
Oh, and she'll have to do it on lower wages. This scenario gets even more dire when you consider what's going to happen to Social Security by the time we make it to When millennials retire, there will be just two. When he finally got a job, his co-workers found out that he washed himself in gas station bathrooms and made him so miserable he quit. He got a job at a grocery store and slept in a shelter while he saved. First stop was subsidized housing in Kirkland, 20 minutes east across the lake. Then a rented house in Tacoma, 45 minutes south, sharing a bedroom with his girlfriend and, eventually, a son.
The first time we met, it was the 27th of the month and Tyrone told me his account was already zeroed out. He had pawned his skateboard the previous night for gas money. The crisis of our generation cannot be separated from the crisis of affordable housing. More people are renting homes than at any time since the late s. But in the 40 years leading up to the recession, rents increased at more than twice the rate of incomes. Rather unsurprisingly, as housing prices have exploded, the number of to year-olds who own homes has plummeted.
You rent for a while to save up for a down payment, then you buy a starter home with your partner, then you move into a larger place and raise a family. Once you pay off the mortgage, your house is either an asset to sell or a cheap place to live in retirement. This worked well when rents were low enough to save and homes were cheap enough to buy.
In one of the most infuriating conversations I had for this article, my father breezily informed me that he bought his first house at I am six years older now than my dad was then. My first house will cost more than 10 years of mine. They built upward, divided homes into apartments and added duplexes and townhomes. But in the s, they stopped building. Cities kept adding jobs and people.
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At first, zoning was pretty modest. In the late s, it finally became illegal to deny housing to minorities. So cities instituted weirdly specific rules that drove up the price of new houses and excluded poor people—who were, disproportionately, minorities. Houses had to have massive backyards. Basically, cities mandated McMansions. But all the political power is held by people who already own homes.
Because when property values go up, so does their net worth. They have every reason to block new construction. They demand two parking spaces for every single unit. True story. The entire system is structured to produce expensive housing when we desperately need the opposite. The housing crisis in our most prosperous cities is now distorting the entire American economy. For most of the 20th century, the way many workers improved their financial fortunes was to move closer to opportunities.
Rents were higher in the boomtowns, but so were wages. Rural areas, meanwhile, still have fewer jobs than they did in For young people trying to find work, moving to a major city is not an indulgence. It is a virtual necessity.
But the soaring rents in big cities are now canceling out the higher wages. Back in , according to a Harvard study, an unskilled worker who moved from a low-income state to a high-income state kept 79 percent of his increased wages after he paid for housing. A worker who made the same move in kept just 36 percent. For the first time in U. This leaves young people, especially those without a college degree, with an impossible choice. They can move to a city where there are good jobs but insane rents. Or they can move somewhere with low rents but few jobs that pay above the minimum wage.
This dilemma is feeding the inequality-generating woodchipper the U. Rather than offering Americans a way to build wealth, cities are becoming concentrations of people who already have it. Millennials who are able to relocate to these oases of opportunity get to enjoy their many advantages: better schools, more generous social services, more rungs on the career ladder to grab on to. In , the Census Bureau reported that young people were less likely to have lived at a different address a year earlier than at any time since Homeownership and migration have been pitched to us as gateways to prosperity because, back when the boomers grew up, they were.
Over the eight months I spent reporting this story, I spent a few evenings at a youth homeless shelter and met unpaid interns and gig-economy bike messengers saving for their first month of rent. During the days I interviewed people like Josh, a year-old affordable housing developer who mentioned that his mother struggles to make ends meet as a contractor in a profession that used to be reliable government work.
Fixing what has been done to us is going to take more than tinkering. Any attempt to recreate the economic conditions the boomers had is just sending lifeboats to a whirlpool. But still, there is already a foot-long list of overdue federal policy changes that would at least begin to fortify our future and reknit the safety net.
Even amid the awfulness of our political moment, we can start to build a platform to rally around. Raise the minimum wage and tie it to inflation. Tilt the tax code away from the wealthy. Right now, rich people can write off mortgage interest on their second home and expenses related to being a landlord or I'm not kidding owning a racehorse. Political efficacy refers to people's perceptions of the political system and politicians . Finally, because less violent communities are usually more equal and have more trust [75,76], the.
To measure social trust and social control two core sets of questions were used from Sampson's seminal paper on collective efficacy  and from Stafford et al. Items relating to political efficacy were from the American and British Political Action Surveys . Neighbourhood security was assessed by items related to frequency of violent occurrences in the neighbourhood . The social capital questionnaire is presented as Additional file 1. The empowerment dimension was not used because it loaded less than 0. Our questionnaire showed sufficient reliability and validity. Cronbach a coefficient for all scales was above 0.
The neighbourhood social capital measure was created as follows: negative items were reverse-coded so that all items ranged from low to high social capital. Weighted and unweighted analysis produced similar results [15,16]. Since each subscale of the social capital. In this way, the subscales were comparable and could be added up to form the neighbourhood-level social capital variable. Items were chosen assuming they reflected the concept of social capital as neighbourhood characteristics. Therefore, questionnaire data on social capital were collected at individual level and then aggregated at area neighbourhood level according to address and residential zip code.
The average number of respondents per neighbourhood was The participants were grouped into 34 neighbourhood areas: 19 neighbourhoods in City 1 and 15 in City 2. The neighbourhoods were then categorized into three equal groups according to tertiles of the social capital score as follows: low from Individual social capital was assessed by measuring social networks and social support. Social networks was considered as the "web" of social relationships surrounding the individual as well as their characteristics, or groups of people who have contact with, or with some.
Figure 3 Distribution of the 34 neighbourhoods areas according to the tertiles of social capital scores: Low social capital neighbourhood area: score from The questionnaire to assess social networks consisted of 5 questions on the person's relationships with family and friends, and their participation in social groups. Social networks questions are presented as Additional file 2. Social support was considered as a system of formal and informal relationships through which individuals receive emotional support, material or information to cope with stressful emotional situations .
Social support was evaluated using a questionnaire consisting of 19 items comprising five dimensions of functional social support: material, affective, emotional, positive social interaction, and information . For each item, the women indicated how often they experienced each type of available support: never, rarely, sometimes, often or always.
The social support and social networks questionnaires have adequate psychometrics properties for the Brazilian population [83,84]. The question used to measure SRH was: "Generally speaking, would you say that your health is: 1- excellent, 2- very good, 3- good, 4- fair, 5- poor". This five-point scale was categorized as "good" excellent, very good, good and "poor" fair, poor SRH. The categorization of SRH adopted in this study was previously used . Participants were divided into two groups according to the SRH at baseline and follow-up. Women who evaluated their health as good at both periods composed the Good SRH group, and Poor SRH group included women who evaluated their general health as poor at baseline and follow-up.
Women who changed their SRH status between baseline and follow-up were separately analyzed because the main outcome of this study was consistent SRH. Changes in SRH during and after pregnancy are associated with many physical alterations and emotional problems . Physical symptoms during pregnancy and shortly after delivery seem to be temporary for the majority of women. However, during the first months of motherhood, childcare is usually associated with tiredness, sleeping problems and low back pain , which are associated with poor SRH .
In this study, the groups of interest were women that, despite the physical and mental changes during pregnancy and postpartum period, had a consistent SRH. The covariates were demographic and socioeconomic characteristics, health-related behaviours and health-reported diseases previous and during pregnancy. Demographic data were age, ethnicity and number of children in family after pregnancy, which were grouped into three.
Age was categorized from 13 to 19, from 20 to 30, and 31 years old or more. Ethnicity, which was based on self-perception of skin colour, was categorized into White, Brown and Black; and number of children in family after pregnancy into 1 child, 2 or 3, and 4 or more children. Socioeconomic characteristics were educational level, occupational context, family income, family structure and housing conditions.
Educational level from 0 to 8 years and 9 or more years of schooling , occupation no paid work - women with no paid work, housewives or unemployed women; paid work - employed women with paid work , and family income from 0 to 1 minimal wage and more than 1 minimal wage , were dichotomized. Family structure was evaluated by marital status and head of family; the family member responsible for the financial support of the household.
Marital status was categorized as married living with partner, has a partner but not living with him and single without partner. Housing conditions was assessed by water plumbing supply inside or outside the house , sewage lack of sewage and pit sewage and general drainage , and number of people per room 1, 2 and 3 or more. Social class was assessed at individual-level and then aggregated at neighbourhood-level. A standard classification of social class used in Brazil was employed. It is based on market power comprising a group of specific indicators and level of education of the head of household composed this variable.
A set of points is assigned to these indicators and a final score defines the socioeconomic groups; A highest , B, C, D, and E lowest. Those with the highest scores represented the highest socioeconomic groups. In this study, the neighbourhoods were categorized as low, moderate and high socioeconomic status, based on the tertiles of the distribution of subjects into class B . Health related behaviours assessed before pregnancy were smoking and alcohol consumption. In addition, the Brazilian version of T-ACE questionnaire was used to detect risky alcohol drinking before pregnancy.
It is based on 5 items concerning self-perception of drinking habits. Two or more positive answers are indicative of increased chance of risky-drinking . Smoking habits was assessed by the following question: "Did you smoke before pregnancy? Self-reported diseases during pregnancy investigated were diabetes, hypertension and urinary infection.
Multilevel logistic regression was used to test the association of neighbourhood and individual social capital with consistent SRH adjusted for neighbourhood and individual-level covariates. Consistency of SRH was a dichotom-ous outcome and logistic regression based on the logit function logarithm of the odds was performed with the predictive quasi likelihood second-order approximation procedures. The multilevel structure comprised individuals level 1 grouped into 34 neighbourhoods level 2.
Continuous variables were compared using the t test and ANOVA, while categorical variables were analyzed using Chi-square test. The MLwiN 2.
Four models were tested. The first model was composed by neighbourhood-level variables at 2nd level - neighbourhood social capital and social class. In the second model, individual social capital variables social network and social support were added. The third model included individual demographic and socioeconomic characteristics, and in the fourth model, the commonest self-reported disease during pregnancy urinary infection was added.
Models 2, 3 and 4 were at 1st and 2nd level. The interaction term composed by neighbourhood social capital and individual social capital was added in the Model 1 to test a possible modifying effect of these variables on the outcome. Separate bivariate analysis was conducted of the women because their SRH status changed between baseline and six months after childbirth. Another reason for not considering them in the multilevel analysis was the low variability of SRH across the neighbourhoods area level variable when SRH was analyzed in four categories.
The variance of SRH among neighbourhoods was tested through multinomial multilevel analysis and did not reach statistical significance.
They were compared regarding socio-demographic characteristics, health-. Continuous variables were compared using the t test, while categorical variables were analyzed using Chi-square test. The comparisons of demographic, socioeconomic and housing conditions characteristics between SRH groups are presented in Table 1. The study women were predominantly head of family Of the sample, Most participants have 2 or 3 children, were Brown ethnicity and aged between 20 and 30 years Table 1. The comparison of health-related behaviours and self-reported diseases between SRH groups is presented in Table 2.
Overall, the participants in both SRH groups reported that they consumed lower levels of alcohol and smoked less than before pregnancy. Whereas the prevalence of diabetes and hypertension before pregnancy was low 1. There were statistically significant differences of individual social capital variables between the SRH groups. In the multivariate analysis four statistical models were developed to test the association of neighbourhood and individual social capital with SRH adjusted for covariates Table 4.
In Model 1, neighbourhood social capital and social class were adjusted for each other. Model 2 included individual social capital variables. In addition, both. Table 1 Socioeconomic and demographic characteristics in the self-rated health groups, State of Rio de Janeiro, Brazil, In Model 3, neighbourhood-level variables were adjusted for individual socioeconomic and demographic covariates.
Low neighbourhood social capital did not remain significantly associated with SRH. Apart from that, the statistical association between low social support and low social networks with poor SRH persisted. Of the socio-demographic covariates, only family. In the final adjusted model Model 4 , neighbourhood-level variables were adjusted for all individual variables, including self-reported urinary infection. Neighbourhood-level variables were not associated with SRH and the association between low social support and low social networks with poor SRH persisted in this final model.
Among socio-demographic variables, water supply outside the house [OR 1. Table 2 Health-related behaviours and self-reported diseases in the self-rated health groups, State of Rio de Janeiro, Brazil, Women from Black and Brown ethnicity were 2. Women with 2 or 3 children and those with 4 or more children were 3. In additional analysis that included the women who changed SRH status, individual social capital was the major differential characteristic among the four groups.
The mean score of affectionate and emotional supports dimensions of social support was higher among women with good SRH, and reduced significantly among those who changed from good SRH to poor SRH. However, no statistical differences were found concerning individual social capital between groups who changed their SRH status from good to poor, or from poor to good SRH. Data are presented in Additional file 3. The interaction term, composed of neighbourhood social capital and individual social capital, was not statistically significant when added to the Model 1, and was therefore removed.
Despite the claim that neighbourhood social capital may be a contextual influence on the health of residents , and that there was a stronger associations between contextual social capital and health in women compared to men [89,90], this study found that neighbourhood social capital was more weakly associated with women's SRH during pregnancy and up to 6 months after delivery than individual social capital and other socio-demographic characteristics. After adjustment for individual variables, no association was found between neighbourhood social capital and SRH.
Therefore, findings of the present study do not support the hypothesis that neighbourhood social capital was related to degree of SRH during pregnancy and up to six months after childbirth. Even though there is evidence of a moderate association between neighbourhood environment and health , some studies did not find an association between neighbourhood social capital and SRH [28,90].
Others found a substantial reduction in the association after adjusting for individual variables [31,91]. Findings from the Stockholm Public Health Cohort study revealed no or moderate associations between contextual social capital and SRH ; the presence or absence of such an association depended on how individual social capital was statistically analyzed. Table 3 Individual social capital scores social support dimensions and social networks in the self-rated health groups, State of Rio de Janeiro, Brazil, In addition, the association was attenuated by perceptions of the neighbourhood and by housing problems .
In a study of 30 districts of Saskatchewan, Canada, the political and civic participation, proxies measures of social capital, were not related to SRH . Our findings differ from other similar studies in Brazil that found an association between neighbourhood characteristics and SRH. In a cohort study involving public university workers, neighbourhood characteristics were associated with SRH after controlling for individual factors such as age, ethnicity, income, education, social class, home, and health conditions [24,93].
Cremonese et al. According to Borges et al. They showed that social trust and civic participation as well as bridging social capital and social support remained associated with.
SRH in a group of adolescents after adjustment for other social capital indicators and confounders. A positive association between social capital and SRH has been frequently reported [20,21,23,32,33]. In most studies, cross-sectional and ecological study designs were employed and demographic characteristics of the samples varied considerably. In addition, the interpretation of evidence is affected by the heterogeneous ways in which social capital was conceived and measured. Moreover, neighbourhood environment has been measured using the number and quality of local services and amenities , or by subjective evaluations obtained directly from local residents about their concerns and perceptions of the neighbourhood about people and place , such as proxy measures or dimensions of neighbourhood social capital - social control, social trust, norms of reciprocity, feelings of safety neighbourhood security , political efficacy and.
Table 4 Adjusted odds ratio OR for poor self-rated health by the neighbourhood-level variables, individual social capital, socioeconomic and demographic variables and self-reported disease, State of Rio de Janeiro, Brazil, Moderate socialcapital 2nd tertil 1. Low socialcapital 1st tertil 1. Therefore, valid comparisons between our findings and those from previous studies are difficult. Although there was no association between neighbourhood social capital and poor SRH in the present study, there was a positive association between social support and social network and SRH.
Therefore, the latter hypothesis was confirmed. The lower the social support and social networks, the higher the likelihood of maintaining poor SRH during pregnancy and 6 months post-partum. That finding accords with previous findings [56,60,95]. The period between pregnancy and 6 months after childbirth is a unique one in most women's life.
Individual social capital appears to be important for women, especially during pregnancy and after delivery. The lack of social support constitutes an important risk factor for maternal well-being during pregnancy . Psychosocial factors are also considered risk factors for undesirable pregnancy outcomes such as low birth weight, prematurity and intrauterine growth retardation [96,97]. Dissatisfaction with partner's support increased the risk of poor SRH  and insufficient social support increased the risk of poor SRH in multiparas .
In the postpartum period, the lack of social support was the most consistent predictor of poor health outcomes . In addition, social networks influenced health behaviours and lifestyle habits during pregnancy, including dietary habits and smoking [28,54,55,98]. Even though smoking during pregnancy was not assessed in the present study, previous studies showed that current smoking did not affect the association between social capital and SRH .
The strong influence of social support and social networks on women's health [31,35] may be due to effective psychosocial resources, particularly social stability and social participation, that provide emotional and instrumental support . During pregnancy and the months thereafter, the association between individual social capital and women's SRH can be explained by the quality of personal and social resources . As personal resources can be very limited compared to those from social ties, especially during pregnancy, social resources are necessary and should be accessible through strong social connections, which represents a sense of attachment or sharing one's sentiments .
Moreover, high social participation was associated with lower odds of poor SRH in women after controlling confounders , probably because women have more ties with their neighbours than do men [,] and are more able to create and. Neighbourhood social capital may be affected by aspects of individual social capital that are associated with health .
Strong ties, such as social support and social networks, seem to mediate the association between neighbourhood social capital and consistent SRH . However, in this study the interaction term was not statistically significant, suggesting that for pregnant women, the combined effect of neighbourhood social capital and individual social capital was not associated with poor SRH. Moreover, neighbourhood social capital was less important for those with consistent SRH during pregnancy and six months postpartum than individual social capital. Women whose SRH status changed during the period of the study were not included in the multilevel analysis.
By excluding them from the analysis, the study population may have been conditioned based on an effect of the exposure. However, the possibility of a 'collider-stratification bias' , a form of selection bias, was rejected by running a model without using postpartum SRH alone as the outcome and including all women regardless of SRH during pregnancy data not shown.
The results were very similar, suggesting that selection bias did not occur. Additional analysis showed that individual social capital differed between groups whose SRH status changed. In addition, the possible influence of individual social capital in women not changing from good to poor levels of SRH over a period of great stress and transition was not confirmed. Conversely, individual social capital was associated with consistent SRH. The findings indicate that it is unlikely that including women who changed their SRH status over time in the overall analysis would affect the results.
The influence of individual and neighbourhood social capital on SRH in women whose pregnancies were aborted or miscarried should be considered in future studies. The findings of this study have several important implications, but are not without limitations. Recruiting pregnant women from public antenatal care units might affect the generalizability of our findings resulting in a homogeneous sample concerning some socioeconomic characteristics. This may explain the lack of association between social class and SRH.
The number of women per neighbourhood was slightly below the ideal and might have affected the power of the study . Our study is limited to pregnant and postpartum women,. A point to be taken into account when considering our findings is that urinary infection was prevalent in our sample The prevalence of urinary infection was slightly higher than in other studies [62,].
The presence of urinary infection was based on self-reports and subject to misreporting. The reported associations in the final model did not change significantly when the variable urinary infection was removed. Future studies should consider collecting data about complications such as 'morning sickness' in early pregnancy or backache, perineal problems during pregnancy and postpartum, and complications of caesarean section postnatally, to validate subjective measures of health.
Positive features of the study were the use of social support and social networks questionnaires with adequate psychometric properties for the Brazilian population. The neighbourhood social capital questionnaire had been used in Brazilian populations and had good reliability. The data collection was standardized and performed by trained interviewers reducing information bias.
In addition, the response rate was high and losses to follow-up were low. There are some points related to the social capital assessment that should to be considered in future studies. One is the measure per si. There is no consensus on how to measure social capital. Contextual social features have been routinely assessed using aggregated measures and indexes, like percentage of poverty or median of income, mainly those available in census databases . In this study, neighbourhood social capital was assessed individually and then aggregated at area level.
However, the characterization of places and neighbourhoods by interviewers was not done. Social epidemiologists need to assess specific characteristics of places and neighbourhoods through primary data collection compositional characteristics , paying attention to resources embedded in social networks . The present study enhances knowledge on social capital and health in several ways. Our findings indicate a relationship between individual social capital and SRH. In addition, multilevel analysis is an adequate statistical approach to evaluate simultaneously the role of neighbourhood-level and individual factors on health.
Above all, more attention was given to low socioeconomic status women, where undesirable pregnancy outcomes rates remain relatively high in other low and middle income countries. Knowledge about how proximal and distal social determinants affect women's health during pregnancy and the initial period of motherhood has important policy implications on the. The identification on what level of social capital was more important to women's health is relevant in developing interventions.
Although social inequalities are viewed as a broad and unspecific determinants of health, our findings suggest that there are specific social risk factors during and after pregnancy that should be taken into account to improve both maternal and child health. Low individual social capital during pregnancy, such as social support and social networks, independently influenced women who had consistently poor SRH whereas neighbourhood social capital did not affect their SRH during pregnancy and the postpartum period.
From pregnancy and up to six months after delivery the effect of individual social capital better explained consistent SRH in women than did neighbourhood social capital. Additional file 3: Socioeconomic and demographic characteristics, health-related behaviours, and individual social capital scores in all groups of SRH. GL was involved in design of the study, acquisition of data, analysis and interpretation of the data, interpretation of the results and drafted the manuscript.
M do CL helped design the study, interpreted the data and reviewed the manuscript. AS was involved in interpretation of the data and revising the manuscript. MV was involved in the conception and design of the study, developed the statisticalframework for data analysis, and helped to draft the manuscript. All authors read and approved the final manuscript. We are gratefulto allparticipants who completed the questionnaires.
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