Writing Sample_Ishita

Writing Sample Ishita Chandra

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Content

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Exploring community inclusivity’s impact on depression in California

Understanding Female worker’s travel pattern in Fruitvale

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01 Exploring community inclusivity’s impact on Depression 1. Research question Does community inclusivity impact the rate of depression in California?

2. Issue

“Depression is a glaring reality for California.” On average, Californians face a high risk of depression.

Some common symptoms of depression are low mood and feeling of loneliness. A constant low mood can thwart people from participating as an equal stakeholder in the city.

It is observed that an inclusive community, where people feel socially supported, have a sense of belonging, and have open communication, can help alleviate depression. To assuage depression, it is essential to understand the relation between inclusivity and depression for city planners.

Though there are many factors related to community inclusion, open communication, social support, sex, and age are examined for this research.

3. Data & Methodology To study the relation, data was drawn from the California health interview survey. Chis data is the largest state-level health survey in the country. The survey is updated annually.

First, step was to choose data for community inclusivity and depression. English proficiency, emotional & social support, age, sex, and depression were selected for this research.

Second, important step was to synthesis the data. For which data types were identified as categorical, nominal and numeric.

Felt depression in the last one month was categorized into six categories. (proxy / skipped=2; all of the time=1; most of the time=2; some of the time=3; a little of the time=4; Not at all=5). For this analysis, responses were re-categorized into two variables, depressed (1,2,3,4) and not depressed (5).

Similarly, English proficiency is categorized into three categories, people who speak only English=1, very well/ well=2, not well/not at all=3. This analysis is re-categorized into two dummy variables: speak/know English (1,2) and don’t speak/ don’t understand English (3).

Likewise, received emotional and social support was categorized into five categories. (always=1, usually=2, sometimes=3, rarely=4, never=5). These were re-categorized into two variables, received emotional & social support (1,2,3,4) and people who did not receive emotional & social support (5).

Self-reported age the only numeric variable. Average age and standard deviation were calculated for this study.

The variables were then tested for association and significance with rate of depression.

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Table 1: Descriptive characteristics N 21,177

Total population

%

Demographic characteristics Depression

Depressed Not depressed

4,316 16,847

20% 80%

English speaking proficiency

Don’t speak/ don’t know English Speak/ know English

1,730 19,447

8% 92%

Emotional & social support

Received support Didn’t receive support

19,101 2,076

90% 10%

Sex

Male Females

9,754 11,423 Mean 54 years

46% 54% SD 20 years

Age

Source: Authors’ calculation for California health interview survey, 2018.

Universe: All adults in California.

Note: 1) Survey weights are not calculated for this table. 2) The data set eliminates proxy or skipped interviews.

Discussion

Table 1, presents the descriptive data of depression and factors related to community inclusion in California. There are some notable results discussed below.

First, on average few people feel depressed in California. 20% share of the total population reported feelings of depression. Second, most of the people living in California can communicate in English.

However, 8% of the total population cannot communicate in English. Third, even though most people feel emotionally and socially supported, 10% share of the total population feels unsupported. Another important observation is that there are more females compared to males in California. The share of female population in California is 8% higher than male population. Lastly, the data shows that the average adult age in California is 54 years.

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Table 2: Factors associated with Depression Total Depressed population

N 4,316

%

Demographic characteristics English speaking proficiency

Don’t speak/ don’t know English Speak/ know English

579 3,737

***33% ***19%

Emotional & social support

Received support Didn’t receive support

3,433 883

***43% ***18%

Sex

Male Females

20% 21%

Age

Depressed Not depressed

1,936 2,380 Mean ***55 years ***48 years

*** p< .001, ** p < .01, * p < .05 Source: Authors’ calculation for California health interview survey, 2018.

Universe: All adults in California.

Note: 1) Survey weights are not calculated for this table. 2) The data set eliminates proxy or skipped interviews.

Results This section discusses the key findings from Table 2, which presents data on association between depression and factors of community inclusivity.

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People who cannot communicate in English are more likely to be depressed.

The table shows that the share of the depressed population who cannot communicate in English is 15% higher than those who can communicate in English. The difference is statistically significant, which ascertains that English proficiency and rate of depression are related.

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People who receive emotional and social support are less likely to be depressed.

The share of depressed population, who receive emotional and social support is 24% less likely to be depressed than the share of depressed population who do not receive emotional and social support. The difference in the rate of depression between the two groups is statistically significant hence we can say that emotional and social support and rate of depression are related.

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On average, younger population are more likely to be depressed than older population.

The average age of people who have depression is 7years older than those who are not depressed. The difference in the age is statistically significant so we can claim that age and rate of depression are related.

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Females are more likely to be depressed than male.

Despite the observation, the difference between the depressed male and female was found to be statistically insignificant. Therefore, we can’t claim the association between rate of depression and sex.

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Limitations Although the factors discussed in the study (age, emotional and social support, English proficiency, sex) are associated with the rate of depression in California, there are other important factors genetics and trauma that may be the cause of a higher rate of depression in California. For future study, genetics can be measured by including presence of a family member with depression as a proxy measure. Another limitation of the study could be false reporting of depression. Social stigma and lack of awareness can be the reason for false reporting.

Conclusion

Chis data was analysed to study the impact of community inclusion on the rate depression. Although the research is limited in important ways - factors like genetics and trauma could be the cause of depression. In conclusion, community inclusion variables considered in this study accept sex, can affect the rate of depression in California.

Bibliography World Bank. “Handbook for Gender-Inclusive Urban Planning and Design.” Accessed November 28, 2020. https://www.worldbank.org/en/topic/urbandevelopment/publication/handbook-forgender-inclusive-urban-planning-and-design.

American Planning Association. “Mind the Gender Gap.” Accessed December 15, 2020. https://www.planning.org/planning/2020/feb/mind-the-gender-gap/.

Time. “Women Are Now the Majority of the U.S. Workforce — But They Still Face Challenges.”

Accessed December 16, 2020. https://time.com/5766787/women-workforce/.

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02 Understanding female worker’s travel Pattern in Fruitvale Introduction

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"Cities have historically been planned and designed for men and by men ." They reflect the traditional gender division of labour, where men were the breadwinners who belonged to the public realm, and women took care of domestic work hence stayed at home. Thus, cities work best for the male 2 population .

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Today, female workforce make up to 50% of the total working population in the United States . Even though there is a shift in the traditional gender roles in the workforce, the female population still faces issues related to safety, mobility, access, economic and social inclusion.

These planning issues and family responsibilities, affect female’s travel pattern to reach their place of work. It’s important to consider that female population use spaces differently than their male counterpart. To ensure sustainable growth of the city, it is imperative to study needs and travel patterns of female population to build an equitable built-environment for all.

This paper studies the travel pattern of females travelling to work in Fruitvale. Fruitvale is a neighbourhood in Oakland, Alameda County, California. The study also draws a comparison of the travel pattern by both the sex from Alameda county.

Key Findings 1. Table 2 - Time of Departure for work by Sex Time of Departure for Work

6am-9am

9-12pm

12 - 4pm

8%

60%

16%

6%

5%

0% 31,285

± 1% 2,29,047

0% 61,443

0% 23,307

± 0% 20,812

5%

64%

17%

7%

5%

0% 16,125

± 1% 2,14,780

0% 56698

0% 22,994

0% 16,095

Male

11%

50%

13%

13%

13%

MOE N = 5,099

± 3% 581

± 6% 2,526

± 3% 648

± 4% 656

± 3% 432

5%

65%

20%

10%

7%

± 4% 100

± 12% 1,422

± 8% 431

± 5% 210

± 4% 163

Male Alameda

MOE N = 384,684

Female MOE N = 334,497

Fruitvale

Female MOE N= 2,187

5am-6am

4pm-12am

Source: ACS Data 2018, 5- Year Table no. B08011; Census tracks: 4065, 4071.01, 4071.02, 4072; Universe: Workers 16 years and over who did not work at home; Note: Margin of error (MOE) expressed at 90% confidence level; Time intervals are divided considering the rush hour of the day

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“Handbook for Gender-Inclusive Urban Planning and Design.”

“Mind the Gender Gap.” 3 “Women Are Now the Majority of the U.S. Workforce — But They Still Face Challenges.”

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Overall, A higher share of female population prefers to leave for work in rush hours (6 to 9 am) than the male population in both the geographies. 65% of the female population travel in rush hours, which is 15% more than the male population. The difference between these two groups is statistically significant, so it can be considered.

Another notable observation is that, a higher share of the female population in Fruitvale leave for work at odd hours compared to the female population in Alameda county. 10% of the female population leave for work between 12 noon to 4 pm in Fruitvale, which is 4% higher than those departing at the same time in Alameda county. The difference between the two groups is statistically insignificant hence cannot be considered.

2. Table 1- Time Taken to travel to work by sex

Time taken to Travel to Work Male Alameda

0-20 min 28%

20-40min 34%

40-60min 19%

60 min< 19%

±1% 107,754

±1% 1,30,900

±1% 74,686

±1% 71,344

33%

34%

17%

16%

±1% 1,09,496

±1% 1,14,004

±1% 57,961

±1% 57,961

25%

47%

16%

13%

MOE N= 5,100

±11% 1,277

±12% 2,374

±10% 795

±10% 653

Female

32%

39%

14%

14%

MOE N= 4,233

±11% 1,363

±12% 1,665

±17% 602

±10% 603

MOE N = 384,684

Female MOE N= 334,498

Male Fruitvale

Source: ACS Data 2018, 5- Year, Table no. B08012; Census tracks: 4065, 4071.01, 4071.02, 4072; Universe (N): Workers 16 years and over who did not work at home; Note: Margin of error (MOE) expressed at 90% confidence level; Time intervals are divided in 20minutes time interval.

Overall, a higher share of the female population prefers shorter travel time to reach work than the male population in both the geographies. In fact, 32% of female population in Fruitvale take up to 20 minutes to travel to work, which is 7% higher than the share of male population. However, the difference between the two groups is statistically insignificant, so it cannot be considered.

Also, a higher share of females in Alameda county take 40 to 60 min to reach their place of work than in Fruitvale. In fact, the share of female population who take 40 to 60min is 3% higher in Alameda county than in Fruitvale. The difference between the two geographies cannot be considered as they are statistically insignificant.

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Figure 1: Percentage of Workers who travel by Public Transit compared by Sex 40%

31%

% of workers 16 years and above

35% 30% 25%

21%

21%

20%

15%

15% 10% 5% 0%

Female

Male Alameda

Fruitville

Source: ACS Data 2018, 5- Year, Table no. B08006, Census tracks: 4065, 4071.01, 4071.02, 4072; Universe: Workers 16 years and above; Note: Margin of error (MOE) expressed at 90% confidence level.

A higher share of female population prefers to travel to work by public transportation as compared to the male population in both the geographies. However, approximately 31% of females in Fruitvale use public transit, which is 10% higher than Alameda county. The differences between the two geographies are statistically significant, so it can be considered.

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Map 2: Percentage of female travelling to work by public transit in 2013

2013

Map 2: Percentage of female travelling to work by public transit in 2018

2018

Source: ACS Data 201& 20138, 5- Year, Table no. B08006, Census tracks: 4065, 4071.01, 4071.02, 4072; Universe: Workers 16 years and above; Note: Margin of error is not included.

In Map 1 & 2, On average, the share of the female population traveling to work by public transit reached 50% in some parts of Alameda county in 2018 as compared to 2013. The growth in the share of the female population using public transit is inconsistent over the years.

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% of workers 16 years and above

Figure 2: Sex of workers by Vehicle Available in Fruitvale 120%

93%

88%

100% 80% 60% 40% 20% 0%

male

female Atleast one car avialable

Source: ACS Data 2018, 5- Year, Table no. B08014, Census tracks: 4065, 4071.01, 4071.02, 4072; Universe: Workers 16 years and above; Note: Margin of error (MOE) expressed at 90% confidence level.

Most female and male workers have a car available to commute to work in Fruitvale. However, 88% of females have at least one car available, which is 5% lesser than the male population. The difference is statistically insignificant hence cannot be considered.

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